Relevant bibliographies by topics / Uncontrolled environments

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Uncontrolled environments'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 January 2023

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Journal articles on the topic "Uncontrolled environments"

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Abbas, Ali, Michael Haslgrübler, Abdul Mannan Dogar, and Alois Ferscha. "Micro Activities Recognition in Uncontrolled Environments." Applied Sciences 11, no. 21 (November 3, 2021): 10327. http://dx.doi.org/10.3390/app112110327.

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Deep learning has proven to be very useful for the image understanding in efficient manners. Assembly of complex machines is very common in industries. The assembly of automated teller machines (ATM) is one of the examples. There exist deep learning models which monitor and control the assembly process. To the best of our knowledge, there exists no deep learning models for real environments where we have no control over the working style of workers and the sequence of assembly process. In this paper, we presented a modified deep learning model to control the assembly process in a real-world environment. For this study, we have a dataset which was generated in a real-world uncontrolled environment. During the dataset generation, we did not have any control over the sequence of assembly steps. We applied four different states of the art deep learning models to control the assembly of ATM. Due to the nature of uncontrolled environment dataset, we modified the deep learning models to fit for the task. We not only control the sequence, our proposed model will give feedback in case of any missing step in the required workflow. The contributions of this research are accurate anomaly detection in the assembly process in a real environment, modifications in existing deep learning models according to the nature of the data and normalization of the uncontrolled data for the training of deep learning model. The results show that we can generalize and control the sequence of assembly steps, because even in an uncontrolled environment, there are some specific activities, which are repeated over time. If we can recognize and map the micro activities to macro activities, then we can successfully monitor and optimize the assembly process.
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Hernández-Rabadán, Deny Lizbeth. "Method for Segmenting Tomato Plants in Uncontrolled Environments." Engineering 04, no. 10 (2012): 599–606. http://dx.doi.org/10.4236/eng.2012.410076.

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Martins, Pedro, José Silvestre Silva, and Alexandre Bernardino. "Multispectral Facial Recognition in the Wild." Sensors 22, no. 11 (June 1, 2022): 4219. http://dx.doi.org/10.3390/s22114219.

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This work proposes a multi-spectral face recognition system in an uncontrolled environment, aiming to identify or authenticate identities (people) through their facial images. Face recognition systems in uncontrolled environments have shown impressive performance improvements over recent decades. However, most are limited to the use of a single spectral band in the visible spectrum. The use of multi-spectral images makes it possible to collect information that is not obtainable in the visible spectrum when certain occlusions exist (e.g., fog or plastic materials) and in low- or no-light environments. The proposed work uses the scores obtained by face recognition systems in different spectral bands to make a joint final decision in identification. The evaluation of different methods for each of the components of a face recognition system allowed the most suitable ones for a multi-spectral face recognition system in an uncontrolled environment to be selected. The experimental results, expressed in Rank-1 scores, were 99.5% and 99.6% in the TUFTS multi-spectral database with pose variation and expression variation, respectively, and 100.0% in the CASIA NIR-VIS 2.0 database, indicating that the use of multi-spectral images in an uncontrolled environment is advantageous when compared with the use of single spectral band images.
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Shafait, Faisal, Ajmal Mian, Mark Shortis, Bernard Ghanem, Phil F. Culverhouse, Duane Edgington, Danelle Cline, Mehdi Ravanbakhsh, James Seager, and Euan S. Harvey. "Fish identification from videos captured in uncontrolled underwater environments." ICES Journal of Marine Science: Journal du Conseil 73, no. 10 (July 18, 2016): 2737–46. http://dx.doi.org/10.1093/icesjms/fsw106.

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Monroy, Javier G., Esteban J. Palomo, Ezequiel López-Rubio, and Javier Gonzalez-Jimenez. "Continuous chemical classification in uncontrolled environments with sliding windows." Chemometrics and Intelligent Laboratory Systems 158 (November 2016): 117–29. http://dx.doi.org/10.1016/j.chemolab.2016.08.011.

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Gunawan, Alexander Agung Santoso, and Reza A. Prasetyo. "Face Recognition Performance in Facing Pose Variation." CommIT (Communication and Information Technology) Journal 11, no. 1 (August 1, 2017): 1. http://dx.doi.org/10.21512/commit.v11i1.1847.

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There are many real world applications of face recognition which require good performance in uncontrolled environments such as social networking, and environment surveillance. However, many researches of face recognition are done in controlled situations. Compared to the controlled environments, face recognition in uncontrolled environments comprise more variation, for example in the pose, light intensity, and expression. Therefore, face recognition in uncontrolled conditions is more challenging than in controlled settings. In thisresearch, we would like to discuss handling pose variations in face recognition. We address the representation issue us ing multi-pose of face detection based on yaw angle movement of the head as extensions of the existing frontal face recognition by using Principal Component Analysis (PCA). Then, the matching issue is solved by using Euclidean distance. This combination is known as Eigenfaces method. The experiment is done with different yaw angles and different threshold values to get the optimal results. The experimental results show that: (i) the more pose variation of face images used as training data is, the better recognition results are, but it also increases the processing time, and (ii) the lower threshold value is, the harder it recognizes a face image, but it also increases the accuracy.
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Edwards, Dalton J., and Logan T. Trujillo. "An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States." Brain Sciences 11, no. 3 (March 5, 2021): 330. http://dx.doi.org/10.3390/brainsci11030330.

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Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4–7 Hz, alpha: 8–13 Hz, low beta: 14–20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments.
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Botero-Valencia, Juan, Luis Castano-Londono, and David Marquez-Viloria. "Indoor Temperature and Relative Humidity Dataset of Controlled and Uncontrolled Environments." Data 7, no. 6 (June 16, 2022): 81. http://dx.doi.org/10.3390/data7060081.

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The large volume of data generated with the increasing development of Internet of Things applications has encouraged the development of a large number of works related to data management, wireless communication technologies, the deployment of sensor networks with limited resources, and energy consumption. Different types of new or well-known algorithms have been used for the processing and analysis of data acquired through sensor networks, algorithms for compression, filtering, calibration, analysis, or variables being common. In some cases, databases available on the network, public government databases, data generated from sensor networks deployed by the authors themselves, or values generated by simulation are used. In the case that the work approach is more related to the algorithm than to the characteristics of the sensor networks, these data source options may have some limitations such as the availability of databases, the time required for data acquisition, the need for the deployment of a real sensors network, and the reliability or characteristics of acquired data. The dataset in this article contains 4,164,267 values of timestamp, indoor temperature, and relative humidity acquired in the months of October and November 2019, with twelve temperature and humidity sensors Xiaomi Mijia at the laboratory of Control Systems and Robotics, and the De La Salle Museum of Natural Sciences, both of the Instituto Tecnológico Metropolitano, Medellín—Colombia. The devices were calibrated in a Metrology Laboratory accredited by the National Accreditation Body of Colombia (Organismo Nacional de Acreditación de Colombia—ONAC). The dataset is available in Mendeley Data repository.
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Hum, Yan Chai, Yee Kai Tee, Wun-She Yap, Hamam Mokayed, Tian Swee Tan, Maheza Irna Mohamad Salim, and Khin Wee Lai. "A contrast enhancement framework under uncontrolled environments based on just noticeable difference." Signal Processing: Image Communication 103 (April 2022): 116657. http://dx.doi.org/10.1016/j.image.2022.116657.

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Barcelo-Ordinas, Jose M., Messaoud Doudou, Jorge Garcia-Vidal, and Nadjib Badache. "Self-calibration methods for uncontrolled environments in sensor networks: A reference survey." Ad Hoc Networks 88 (May 2019): 142–59. http://dx.doi.org/10.1016/j.adhoc.2019.01.008.

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Dissertations / Theses on the topic "Uncontrolled environments"

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Fu, Y. "Face recognition in uncontrolled environments." Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1468901/.

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This thesis concerns face recognition in uncontrolled environments in which the images used for training and test are collected from the real world instead of laboratories. Compared with controlled environments, images from uncontrolled environments contain more variation in pose, lighting, expression, occlusion, background, image quality, scale, and makeup. Therefore, face recognition in uncontrolled environments is much more challenging than in controlled conditions. Moreover, many real world applications require good recognition performance in uncontrolled environments. Example applications include social networking, human-computer interaction and electronic entertainment. Therefore, researchers and companies have shifted their interest from controlled environments to uncontrolled environments over the past seven years. In this thesis, we divide the history of face recognition into four stages and list the main problems and algorithms at each stage. We find that face recognition in unconstrained environments is still an unsolved problem although many face recognition algorithms have been proposed in the last decade. Existing approaches have two major limitations. First, many methods do not perform well when tested in uncontrolled databases even when all the faces are close to frontal. Second, most current algorithms cannot handle large pose variation, which has become a bottleneck for improving performance. In this thesis, we investigate Bayesian models for face recognition. Our contributions extend Probabilistic Linear Discriminant Analysis (PLDA) [Prince and Elder 2007]. In PLDA, images are described as a sum of signal and noise components. Each component is a weighted combination of basis functions. We firstly investigate the effect of degree of the localization of these basis functions and find better performance is obtained when the signal is treated more locally and the noise more globally. We call this new algorithm multi-scale PLDA and our experiments show it can handle lighting variation better than PLDA but fails for pose variation. We then analyze three existing Bayesian face recognition algorithms and combine the advantages of PLDA and the Joint Bayesian Face algorithm [Chen et al. 2012] to propose Joint PLDA. We find that our new algorithm improves performance compared to existing Bayesian face recognition algorithms. Finally, we propose Tied Joint Bayesian Face algorithm and Tied Joint PLDA to address large pose variations in the data, which drastically decreases performance in most existing face recognition algorithms. To provide sufficient training images with large pose difference, we introduce a new database called the UCL Multi-pose database. We demonstrate that our Bayesian models improve face recognition performance when the pose of the face images varies.
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Yao, Yi. "Hand gesture recognition in uncontrolled environments." Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/74268/.

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Human Computer Interaction has been relying on mechanical devices to feed information into computers with low efficiency for a long time. With the recent developments in image processing and machine learning methods, the computer vision community is ready to develop the next generation of Human Computer Interaction methods, including Hand Gesture Recognition methods. A comprehensive Hand Gesture Recognition based semantic level Human Computer Interaction framework for uncontrolled environments is proposed in this thesis. The framework contains novel methods for Hand Posture Recognition, Hand Gesture Recognition and Hand Gesture Spotting. The Hand Posture Recognition method in the proposed framework is capable of recognising predefined still hand postures from cluttered backgrounds. Texture features are used in conjunction with Adaptive Boosting to form a novel feature selection scheme, which can effectively detect and select discriminative texture features from the training samples of the posture classes. A novel Hand Tracking method called Adaptive SURF Tracking is proposed in this thesis. Texture key points are used to track multiple hand candidates in the scene. This tracking method matches texture key points of hand candidates within adjacent frames to calculate the movement directions of hand candidates. With the gesture trajectories provided by the Adaptive SURF Tracking method, a novel classi�er called Partition Matrix is introduced to perform gesture classification for uncontrolled environments with multiple hand candidates. The trajectories of all hand candidates extracted from the original video under different frame rates are used to analyse the movements of hand candidates. An alternative gesture classifier based on Convolutional Neural Network is also proposed. The input images of the Neural Network are approximate trajectory images reconstructed from the tracking results of the Adaptive SURF Tracking method. For Hand Gesture Spotting, a forward spotting scheme is introduced to detect the starting and ending points of the prede�ned gestures in the continuously signed gesture videos. A Non-Sign Model is also proposed to simulate meaningless hand movements between the meaningful gestures. The proposed framework can perform well with unconstrained scene settings, including frontal occlusions, background distractions and changing lighting conditions. Moreover, it is invariant to changing scales, speed and locations of the gesture trajectories.
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Huerta, Casado Ivan. "Foreground Object Segmentation and Shadow Detection for Video Sequences in Uncontrolled Environments." Doctoral thesis, Universitat Autònoma de Barcelona, 2010. http://hdl.handle.net/10803/5797.

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Aquesta tesis esta dividida en dos parts principalment. A la primera, es presenta un estudi dels problemes que es poden trobar en la segmentació per moviment, basant-se en aquest estudi es presenta un algoritme genèric el qual es capaç de solucionar d'una forma acurada la majoria dels problemes que es poden trobar en aquest tipus de segmentació. En la segona part, es tracta el tema de les ombres en profunditat. Primer, es presenta un algoritme bottom-up basat en un detector de ombres cromàtiques el qual es capaç no només de solucionar les ombres que es troben a la penombra, sinó també les ombres que podem trobar a l'umbra. Segon, es presenta un sistema topdown basat en un sistema de tracking per tal de trackejar les ombres i d'aquesta manera millorar la detecció de les ombres cromàtiques.
En la nostra primera contribució, presentem un anàlisis del possibles problemes que trobem en la segmentació per moviment quan utilitzem el color, els gradients, o la intensitat. La nostra segona aportació es una arquitectura hibrida la qual pot solucionar els principals problemes observats en l'anàlisi, mitjançant la fusió de (i) la informació obtinguda per aquestes tres cues, i (ii) un algoritme de diferencia temporal. Per un costat, em aconseguit millorat els models de color i de gradients per que puguin solucionar tant el problemes amb els canvis de il·luminació global i local (com les ombres no cromàtiques) i els camuflatges en intensitat. A més a més, la informació local es explotada per tal de solucionar el problema dels camuflatges en croma. Per una altra banda, la intensitat es aplicada quan el color i els gradients no estan disponibles degut a problemes en la obtenció d'aquests (es troben fora del rang dinàmic). Addicionalment, la diferencia temporal es inclosa en la segmentació per moviment en el moment en que cap de les cues estudiades no estan disponibles, com per exemple quan el fons de la imatge no es visible en el període de entrenament. Per últim en aquesta primera part, el nostre algoritme també ha de solucionar el problema de les segmentacions fantasma. Com a resultat, el nostre algoritme obté una segmentació robusta i acurada tant en escenaris d'interior com d'exterior, tal i com s'ha demostrat tant quantitativament com qualitativament en els resultats experimentals, mitjançant la comparació del nostre algoritme amb els més coneguts algoritmes de l'estat de l'art.
La segmentació en moviment té que tenir en compte el problema de les ombres per tal de evitar distorsions quan intentem segmentar els objectes en moviment. Però molts dels algoritmes que son capaços de detectar les ombres solament son capaços de detectar les ombres a la penombra. En conseqüència, aquestes tècniques no son capaces de detectar les ombres a l'umbra les quals son normalment detectades com part dels objectes en moviment.
En aquesta tesis presentem primer una innovadora tècnica que es basa en els models de gradients i de color per tal de separar aquestes ombres cromàtiques dels objectes en moviment. Primerament, construïm tant un model de color en forma de con, com també un model de gradient els quals son invariant a les cromaticitats per tal d'aconseguir fer una segmentació automàtica a la vegada que totes les possibles ombres son detectades. En un segon pas, les regions que poden ser ombres son agrupades considerant "l'efecte blau" i les particions obtingudes mitjançant els gradients. Finalment, analitzem (i) les similituds temporals entre els les estructures locals dels gradients i (ii) les similituds espacials entre els angles cromàtics i les distorsions de la lluminositat de totes les ombres potencials per tal d'identificar les ombres a la umbra.
Segon, en el procés top-down després de la detecció dels objectes i les ombres els dos son seguits usant un filtre de Kalman, per d'aquesta manera millorar la detecció de lesombrescromàtiques. Primerament, l'algoritme fa una associacióentre elsblobs (foreground i ombres) i els filtres de Kalman. Segon, es realitza un anàlisis dels possibles casos entre las associacions obtingudes anteriorment, i a més a més es tracten les oclusions mitjançant un Model Probabilístic d'Aparença. Basant-se en aquesta associació es busca la consistència temporal entre els foregrounds, les ombres, i els seus respectius filtres de Kalman. A partir d'aquesta nova associació son estudiats diferents casos, com a resultat les ombres cromàtiques que s'havien perdut son detectades. Finalment, els resultats son utilitzats com a feedback per millorar la detecciódela ombra i del objecte.
Pel contrari que altres algoritmes el nostre mètode no fa cap assumpcióapriori sobre la localitzaciódelacàmera, les geometries o les textures de les superfícies, les formes o els possibles tipus de ombres, objectes o de fons de la imatge. Els resultats experimentals mostren la performance i la precisió del nostre algoritme en la detecció de les ombres cromàtiques en diferents materials i amb diferents condicions de il·luminació.
This Thesis is mainly divided in two parts. The first one presents a study of motion segmentation problems. Based on this study, a novel algorithm for mobile-object segmentation from a static background scene is also presented. This approach is demonstrated robust and accurate under most of the common problems in motion segmentation. The second one tackles the problem of shadows in depth. Firstly, a bottom-up approach based on a chromatic shadow detector is presented to deal with umbra shadows. Secondly, a top-down approach based on a tracking system has been developed in order to enhance the chromatic shadow detection.
In our first contribution, a case analysis of motion segmentation problems is presented by taking into account the problems associated with different cues, namely colour, edge and intensity. Our second contribution is a hybrid architecture which handles the main problems observed in such a case analysis, by fusing (i) the knowledge from these three cues and (ii) a temporal difference algorithm. On the one hand, we enhance the colour and edge models to solve both global/local illumination changes (shadows and highlights) and camouflage in intensity. In addition, local information is exploited to cope with a very challenging problem such as the camouflage in chroma. On the other hand, the intensity cue is also applied when colour and edge cues are not available, such as when beyond the dynamic range. Additionally, temporal difference is included to segment motion when these three cues are not available, such as that background not visible during the training period. Lastly, the approach is enhanced for allowing ghost detection. As a result, our approach obtains very accurate and ro¬bust motion segmentation in both indoor and outdoor scenarios, as quantitatively and qualitatively demonstrated in the experimental results, by comparing our approach with most best-known state-of-the-art approaches.
Motion Segmentation has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects.
Firstly, a bottom-up approach for detection and removal of chromatic moving shadows in surveillance scenarios is proposed. Secondly, a top-down approach based on kalman filters to detect and track shadows has been developed in order to enhance the chromatic shadow detection. In the Bottom-up part, the shadow detection approach applies a novel technique based on gradient and colour models for separating chromatic moving shadows from moving objects.
Well-known colour and gradient models are extended and improved into an invariant colour cone model and an invariant gradient model, respectively, to perform automatic segmentation while detecting potential shadows. Hereafter, the regions corresponding to potential shadows are grouped by considering "a bluish effect" and an edge partitioning. Lastly, (i) temporal similarities between local gradient structures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows.
In the top-down process, after detection of objects and shadows both are tracked using Kalman filters, in order to enhance the chromatic shadow detection, when it fails to detect a shadow. Firstly, this implies a data association between the blobs (foreground and shadow) and Kalman filters. Secondly, an event analysis of the different data association cases is performed, and occlusion handling is managed by a Probabilistic Appearance Model (PAM). Based on this association, temporal consistency is looked for the association between foregrounds and shadows and their respective Kalman Filters. From this association several cases are studied, as a result lost chromatic shadows are correctly detected. Finally, the tracking results are used as feedback to improve the shadow and object detection.
Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions.
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Moore, Kristin Suzanne. "Comparison of eye movement data to direct measures of situation awareness for development of a novel measurement technique in dynamic, uncontrolled test environments." Connect to this title online, 2009. http://etd.lib.clemson.edu/documents/1263402095/.

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Fathi, Kazerouni Masoud [Verfasser], and Klaus-Dieter [Gutachter] Kuhnert. "Fully-automated plant recognition systems in challenging controlled and uncontrolled environments using classical and Deep Learning methods / Masoud Fathi Kazerouni ; Gutachter: Klaus-Dieter Kuhnert." Siegen : Universitätsbibliothek der Universität Siegen, 2019. http://d-nb.info/1208506811/34.

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Svens, Lisa. "Mathematical Analysis of Intensity Based Segmentation Algorithms with Implementations on Finger Images in an Uncontrolled Environment." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-43650.

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The main task of this thesis is to perform image segmentation on images of fingers to partition the image into two parts, one with the fingers and one with all that is not fingers. First, we present the theory behind several well-used image segmentation methods, such as SNIC superpixels, the k-means algorithm, and the normalised cut algorithm. These have then been implemented and tested on images of fingers and the results are shown. The implementations are unfortunately not stable and give segmentations of varying results.
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Braga, Marilita Gnecco de Camargo. "The vehicle driver's perception of attributes of the road environment that influence safety at four-arm uncontrolled junctions." Thesis, Imperial College London, 1990. http://hdl.handle.net/10044/1/47784.

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BLACK, DAVID PAUL. "SYNERGIES IN WITHIN- AND BETWEEN-PERSON INTERLIMB RHYTHMIC COORDINATION: EFFECTS OF COORDINATION STABILITY AND ENVIRONMENTAL ANCHORING." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1129553094.

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Yu, Xiezhi. "Assessment and bioremediation of solis contaminated by uncontrolled recycling of electronic-waste at Guiyu, SE China." HKBU Institutional Repository, 2008. http://repository.hkbu.edu.hk/etd_ra/876.

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Junior, Jozias Rolim de Araújo. "Reconhecimento multibiométrico baseado em imagens de face parcialmente ocluídas." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/100/100131/tde-24122018-011508/.

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Com o avanço da tecnologia, as estratégias tradicionais para identificação de pessoas se tornaram mais suscetíveis a falhas. De forma a superar essas dificuldades algumas abordagens vêm sendo propostas na literatura. Dentre estas abordagens destaca-se a Biometria. O campo da Biometria abarca uma grande variedade de tecnologias usadas para identificar ou verificar a identidade de uma pessoa por meio da mensuração e análise de aspectos físicos e/ou comportamentais do ser humano. Em função disso, a biometria tem um amplo campo de aplicações em sistemas que exigem uma identificação segura de seus usuários. Os sistemas biométricos mais populares são baseados em reconhecimento facial ou em impressões digitais. Entretanto, existem sistemas biométricos que utilizam a íris, varredura de retina, voz, geometria da mão e termogramas faciais. Atualmente, tem havido progresso significativo em reconhecimento automático de face em condições controladas. Em aplicações do mundo real, o reconhecimento facial sofre de uma série de problemas nos cenários não controlados. Esses problemas são devidos, principalmente, a diferentes variações faciais que podem mudar muito a aparência da face, incluindo variações de expressão, de iluminação, alterações da pose, assim como oclusões parciais. Em comparação com o grande número de trabalhos na literatura em relação aos problemas de variação de expressão/iluminação/pose, o problema de oclusão é relativamente negligenciado pela comunidade científica. Embora tenha sido dada pouca atenção ao problema de oclusão na literatura de reconhecimento facial, a importância deste problema deve ser enfatizada, pois a presença de oclusão é muito comum em cenários não controlados e pode estar associada a várias questões de segurança. Por outro lado, a Multibiométria é uma abordagem relativamente nova para representação de conhecimento biométrico que visa consolida múltiplas fontes de informação visando melhorar a performance do sistema biométrico. Multibiométria é baseada no conceito de que informações obtidas a partir de diferentes modalidades ou da mesma modalidade capturada de diversas formas se complementam. Consequentemente, uma combinação adequada dessas informações pode ser mais útil que o uso de informações obtidas a partir de qualquer uma das modalidades individualmente. A fim de melhorar a performance dos sistemas biométricos faciais na presença de oclusão parciais será investigado o emprego de diferentes técnicas de reconstrução de oclusões parciais de forma a gerar diferentes imagens de face, as quais serão combinadas no nível de extração de característica e utilizadas como entrada para um classificador neural. Os resultados demonstram que a abordagem proposta é capaz de melhorar a performance dos sistemas biométricos baseados em face parcialmente ocluídas
With the advancement of technology, traditional strategies for identifying people have become more susceptible to failures. In order to overcome these difficulties, some approaches have been proposed in the literature. Among these approaches, Biometrics stands out. The field of biometrics covers a wide range of technologies used to identify or verify a person\'s identity by measuring and analyzing physical and / or behavioral aspects of the human being. As a result, a biometry has a wide field of applications in systems that require a secure identification of its users. The most popular biometric systems are based on facial recognition or fingerprints. However, there are biometric systems that use the iris, retinal scan, voice, hand geometry, and facial thermograms. Currently, there has been significant progress in automatic face recognition under controlled conditions. In real world applications, facial recognition suffers from a number of problems in uncontrolled scenarios. These problems are mainly due to different facial variations that can greatly change the appearance of the face, including variations in expression, illumination, posture, as well as partial occlusions. Compared with the large number of papers in the literature regarding problems of expression / illumination / pose variation, the occlusion problem is relatively neglected by the research community. Although attention has been paid to the occlusion problem in the facial recognition literature, the importance of this problem should be emphasized, since the presence of occlusion is very common in uncontrolled scenarios and may be associated with several safety issues. On the other hand, multibiometry is a relatively new approach to biometric knowledge representation that aims to consolidate multiple sources of information to improve the performance of the biometric system. Multibiometry is based on the concept that information obtained from different modalities or from the same modalities captured in different ways complement each other. Accordingly, a suitable combination of such information may be more useful than the use of information obtained from any of the individuals modalities. In order to improve the performance of facial biometric systems in the presence of partial occlusion, the use of different partial occlusion reconstruction techniques was investigated in order to generate different face images, which were combined at the feature extraction level and used as input for a neural classifier. The results demonstrate that the proposed approach is capable of improving the performance of biometric systems based on partially occluded faces
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Books on the topic "Uncontrolled environments"

1

Foley, W. J. Closeout of IE bulletin 80-10: Contamination of nonradioactive system and resulting potential for unmonitored, uncontrolled release of radioactivity to the environment. Washington, DC: Division of Operational Events Assessment, Office of Nuclear Reactor Regulation, U.S. Nuclear Regulatory Commission, 1990.

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Babina, Ol'ga. Theory, methodology and practice of regional strategic planning. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1738755.

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In the monograph, the region is presented as a complex, multilevel socio-economic system consisting of many heterogeneous, interacting economic entities of different levels (economic agents and markets, management, resources and economic processes), jointly organizing reproduction processes embedded in the economic space of the national economy on the local territory. Currently, the role of rational management of the socio-economic development of the region is increasing. In such conditions, it is advisable to use strategic planning, which, in turn, has increasingly been carried out using a simulation model. The simulation model in regional strategic planning allows government agencies to predict their activities in the presence of various controlled and uncontrolled factors of the external and internal environment. In this study, the list of principles of strategic planning focused on the processes of strategic planning of the region using the method of simulation modeling is supplemented. A methodology for organizing strategic planning processes at the meso-level using simulation modeling technology is proposed. For a wide range of readers interested in the problems of regional strategic planning.
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United States. Congress. House. Committee on Government Operations. Environment, Energy, and Natural Resources Subcommittee. The uncontrolled export of unregistered pesticides: Hearing before the Environment, Energy, and Natural Resources Subcommittee of the Committee on Government Operations, House of Representatives, One Hundred First Congress, first session, May 3, 1989. Washington: U.S. G.P.O., 1989.

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United States. Congress. House. Committee on Government Operations. Environment, Energy, and Natural Resources Subcommittee. The uncontrolled export of unregistered pesticides: Hearing before the Environment, Energy, and Natural Resources Subcommittee of the Committee on Government Operations, House of Representatives, One Hundred First Congress, first session, May 3, 1989. Washington: U.S. G.P.O., 1989.

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United States. Congress. House. Committee on Government Operations. Environment, Energy, and Natural Resources Subcommittee. The uncontrolled export of unregistered pesticides: Hearing before the Environment, Energy, and Natural Resources Subcommittee of the Committee on Government Operations, House of Representatives, One Hundred First Congress, first session, May 3, 1989. Washington: U.S. G.P.O., 1989.

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United States. Congress. House. Committee on Merchant Marine and Fisheries. Subcommittee on Fisheries and Wildlife Conservation and the Environment. High seas driftnet fishing: Hearing before the Subcommittee on Fisheries and Wildlife Conservation and the Environment of the Committee on Merchant Marine and Fisheries, House of Representatives, One Hundred Second Congress, first session, on the devastating effects that uncontrolled largescale driftnetting has had on the marine resources of the northern Pacific Ocean, August 6, 1991--Seattle, Washington. Washington: U.S. G.P.O., 1991.

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Oliveri, Stephen R. Field Safety in Uncontrolled Environments: A Process-Based Guidebook. American Association of Petroleum Geologists, 2005.

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Taylor, Elaine. Uncontrolled Environment. Dorrance Publishing Co., 2018.

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Center for Environmental Research Information (U.S.), ed. Approaches for remediation of uncontrolled wood preserving sites. Cincinnati, OH: Center for Environmental Research Information, Office of Research and Development, U.S. Environmental Protection Agency, 1990.

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Bulut, Mehmet, and Cem Korkut, eds. Döngüsel Ekonomi ve Sürdürülebilir Hayat. Turkish Academy of Sciences, 2022. http://dx.doi.org/10.53478/tuba.978-605-2249-97-0.

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The “circular economy” practices within the concept of sustainability offer solutions to the problem of uncontrolled production and irresponsible consumption that the world is trying to overcome. Approaches are being developed within the framework of circular economy in many areas from economy to environment, from education to local government policies, from finance to trade. The book “Circular Economy and Sustainable Living” discusses the circular economy conceptually and questions its necessity. Afterwards, it focuses on the applications of this concept with chapters written by experts in the field. The peculiarity of this book is that it does not focus solely on the definition of the circular economy. Besides economic issues such as capital markets, value chains, labor market, cryptocurrencies, management of enterprises, the book also includes practices in education and environment. We hope that the book will contribute to the solution of the global economic and environmental problems experienced by the world with detections and suggestions.
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Book chapters on the topic "Uncontrolled environments"

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Gangonda, Siddheshwar S., Prashant P. Patavardhan, and Kailash J. Karande. "Analysis of Face Recognition Algorithms for Uncontrolled Environments." In Advances in Intelligent Systems and Computing, 919–26. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1513-8_93.

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Coimbra, Miguel, and João Paulo Silva Cunha. "Vital Responder – Wearable Sensing Challenges in Uncontrolled Critical Environments." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 45–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32778-0_4.

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Reck, Ryan, and Sherine Antoun. "Autonomous Robot Navigation with Fuzzy Logic in Uncontrolled Environments." In Advances in Intelligent Systems and Computing, 275–83. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32523-7_18.

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Conde, Cristina, Isaac Martin de Diego, and Enrique Cabello. "Face Recognition in Uncontrolled Environments, Experiments in an Airport." In E-Business and Telecommunications, 20–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35755-8_2.

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Santiago Ramírez, Everardo, J. C. Acosta-Guadarrama, Jose Manuel Mejía Muñoz, Josue Dominguez Guerrero, and J. A. Gonzalez-Fraga. "Facial Re-identification on Non-overlapping Cameras and in Uncontrolled Environments." In Lecture Notes in Computer Science, 170–82. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21077-9_16.

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Castelblanco, Alejandra, Jesus Solano, Christian Lopez, Esteban Rivera, Lizzy Tengana, and Martín Ochoa. "Machine Learning Techniques for Identity Document Verification in Uncontrolled Environments: A Case Study." In Lecture Notes in Computer Science, 271–81. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49076-8_26.

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Bakshi, Akshay, Sudhanshu Gulhane, Tanish Sawant, Vijay Sambhe, and Sandeep S. Udmale. "ALPR - An Intelligent Approach Towards Detection and Recognition of License Plates in Uncontrolled Environments." In Lecture Notes in Computer Science, 253–69. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-24848-1_18.

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Fields, Lindsay, and John Licato. "Combatting Conspiratorial Thinking with Controlled Argumentation Dialogue Environments." In The Pandemic of Argumentation, 291–309. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-91017-4_15.

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AbstractThe COVID-19 pandemic has been associated with an explosion in misinformation, leading to increased interest in methods to combat the failures in critical thinking which make such misinformation so powerful. In combatting misinformation, simply throwing uncontrolled argumentation at the problem is often counter-productive, partially because the means by which people evaluate arguments are highly subject to cognitive biases. Such biases which promote jumping to unwarranted conclusions have been shown to correlate with conspiratorial belief. We consider the use of Controlled Argumentation Dialogue Environments (CADEs) as a means to mitigate cognitive biases which contribute to belief in COVID-19 conspiracy theories. We will discuss Warrant Game (WG) and Warrant Game for Analogies (WG-A), CADEs in which two arguers are presented with a divisive issue and two competing positions on that issue. They then compete by iteratively improving warrants for their arguments and attacking those of their opponents. The warrant, when made explicit, makes it easier to determine key features typically associated with argument strength and may reveal hidden assumptions or fundamental reasoning incompatibilities. By presenting an issue and positions which relate to conspiratorial thinking, CADEs may operate as an educational tool for breaking conspiratorial belief into core values and building cognitive skills.
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Yao, Yi, and Chang-Tsun Li. "Real-Time Hand Gesture Recognition for Uncontrolled Environments Using Adaptive SURF Tracking and Hidden Conditional Random Fields." In Advances in Visual Computing, 542–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41939-3_53.

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Ding, Yuqi, Nianyi Li, S. Susan Young, and Jinwei Ye. "Efficient 3D Face Recognition in Uncontrolled Environment." In Advances in Visual Computing, 430–43. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33720-9_33.

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Conference papers on the topic "Uncontrolled environments"

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Podilchuk, Christine, William Hulbert, Ralph Flachsbart, and Lev Barinov. "Face recognition for uncontrolled environments." In SPIE Defense, Security, and Sensing, edited by B. V. K. Vijaya Kumar, Salil Prabhakar, and Arun A. Ross. SPIE, 2010. http://dx.doi.org/10.1117/12.851986.

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Mirzadeh, Seyed Iman, Jessica Ardo, Ramin Fallahzadeh, Bryan Minor, Lorraine Evangelista, Diane Cook, and Hassan Ghasemzadeh. "LabelMerger: Learning Activities in Uncontrolled Environments." In 2019 First International Conference on ​Transdisciplinary AI (TransAI). IEEE, 2019. http://dx.doi.org/10.1109/transai46475.2019.00019.

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Aghajanian, Jania, and Simon J. D. Prince. "Face Pose Estimation in Uncontrolled Environments." In British Machine Vision Conference 2009. British Machine Vision Association, 2009. http://dx.doi.org/10.5244/c.23.76.

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Simone, Gabriele, Marius Pedersen, and Jon Yngve Hardeberg. "Measuring perceptual contrast in uncontrolled environments." In 2010 2nd European Workshop on Visual Information Processing (EUVIP). IEEE, 2010. http://dx.doi.org/10.1109/euvip.2010.5699114.

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Zeng, Pingping, Yu-Jin Zhang, and Fei Duan. "Gender classification system in uncontrolled environments." In IS&T/SPIE Electronic Imaging, edited by Juha Röning, David P. Casasent, and Ernest L. Hall. SPIE, 2011. http://dx.doi.org/10.1117/12.872320.

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Cheng Zhong, Zhenan Sun, Tieniu Tan, and Zhaofeng He. "Robust 3D face recognition in uncontrolled environments." In 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2008. http://dx.doi.org/10.1109/cvpr.2008.4587646.

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Germann, Marcel, Tiberiu Popa, Remo Ziegler, Richard Keiser, and Markus Gross. "Space-Time Body Pose Estimation in Uncontrolled Environments." In 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT). IEEE, 2011. http://dx.doi.org/10.1109/3dimpvt.2011.38.

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Moraes, André Ribeiro, and Clodoaldo Aparecido de Moraes Lima. "Facial Detection in Uncontrolled Environments: Systematic Literature Review." In SBSI 2021: XVII Brazilian Symposium on Information Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3466933.3466992.

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da Silva Vieira, Gabriel, Fabrizzio A. A. M. N. Soares, Junio Cesar de Lima, Gustavo T. Laureano, Samuel A. Santos, Ronaldo M. Costa, and Rogerio Salvini. "Trunk Detection and Tree Disparity Calculation in Uncontrolled Environments." In 2019 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2019. http://dx.doi.org/10.1109/iscc47284.2019.8969574.

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Nefian, Ara V., Mehdi Khosravi, and Monson H. Hayes III. "Real-time detection of human faces in uncontrolled environments." In Electronic Imaging '97, edited by Jan Biemond and Edward J. Delp III. SPIE, 1997. http://dx.doi.org/10.1117/12.263232.

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Reports on the topic "Uncontrolled environments"

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Hugh I. Henderson, Jensen Zhang, James B. Cummings, and Terry Brennan. Mitigating the Impacts of Uncontrolled Air Flow on Indoor Environmental Quality and Energy Demand in Non-Residential Buildings. Office of Scientific and Technical Information (OSTI), July 2006. http://dx.doi.org/10.2172/924486.

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Foley, W., R. Dean, and D. Hennick. Closeout of IE Bulletin 80-10: Contamination of nonradioactive system and resulting potential for unmonitored, uncontrolled release of radioactivity to the environment. Office of Scientific and Technical Information (OSTI), February 1990. http://dx.doi.org/10.2172/7011675.

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