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Dissertations / Theses on the topic 'Binary vector'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Jiang, Fuhua. "SVM-Based Negative Data Mining to Binary Classification." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_diss/8.

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The properties of training data set such as size, distribution and the number of attributes significantly contribute to the generalization error of a learning machine. A not well-distributed data set is prone to lead to a partial overfitting model. Two approaches proposed in this dissertation for the binary classification enhance useful data information by mining negative data. First, an error driven compensating hypothesis approach is based on Support Vector Machines (SVMs) with (1+k)-iteration learning, where the base learning hypothesis is iteratively compensated k times. This approach prod

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2

Rogers, Spencer David. "Support Vector Machines for Classification and Imputation." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3215.

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Support vector machines (SVMs) are a powerful tool for classification problems. SVMs have only been developed in the last 20 years with the availability of cheap and abundant computing power. SVMs are a non-statistical approach and make no assumptions about the distribution of the data. Here support vector machines are applied to a classic data set from the machine learning literature and the out-of-sample misclassification rates are compared to other classification methods. Finally, an algorithm for using support vector machines to address the difficulty in imputing missing categorical data i

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Brady, Patrick. "Internal representation and biological plausibility in an artificial neural network." Thesis, Brunel University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.311273.

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4

Andreola, Rafaela. "Support Vector Machines na classificação de imagens hiperespectrais." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2009. http://hdl.handle.net/10183/17894.

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É de conhecimento geral que, em alguns casos, as classes são espectralmente muito similares e que não é possível separá-las usando dados convencionais em baixa dimensionalidade. Entretanto, estas classes podem ser separáveis com um alto grau de acurácia em espaço de alta dimensão. Por outro lado, classificação de dados em alta dimensionalidade pode se tornar um problema para classificadores paramétricos, como o Máxima Verossimilhança Gaussiana (MVG). Um grande número de variáveis que caracteriza as imagens hiperespectrais resulta em um grande número de parâmetros a serem estimados e, geralment

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Axén, Maja, and Jennifer Karlberg. "Binary Classification for Predicting Customer Churn." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-171892.

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Predicting when a customer is about to turn to a competitor can be difficult, yet extremely valuable from a business perspective. The moment a customer stops being considered a customer is known as churn, a widely researched topic in several industries when dealing with subscription-services. However, in industries with non-subscription services and products, defining churn can be a daunting task and the existing literature does not fully cover this field. Therefore, this thesis can be seen as a contribution to current research, specially when not having a set definition for churn. A definitio

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Oosthuizen, Surette. "Variable selection for kernel methods with application to binary classification." Thesis, Stellenbosch : University of Stellenbosch, 2008. http://hdl.handle.net/10019.1/1301.

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Thesis (PhD (Statistics and Actuarial Science))—University of Stellenbosch, 2008.<br>The problem of variable selection in binary kernel classification is addressed in this thesis. Kernel methods are fairly recent additions to the statistical toolbox, having originated approximately two decades ago in machine learning and artificial intelligence. These methods are growing in popularity and are already frequently applied in regression and classification problems. Variable selection is an important step in many statistical applications. Thereby a better understanding of the problem being in

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Hedlund, Henrik. "Predicting Satisfaction in Customer Support Chat : Opinion Mining as a Binary Classification Problem." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-300165.

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The study explores binary classification with Support Vector Machines as means to predict a satisfaction score based on customer surveys in the customer supportdomain. Standard feature selection methods and their impact on results are evaluated and a feature scoring metric Log Odds Ratio is implemented for addressingasymmetrical class distributions. Results show that the feature selection andscoring methods implemented improve performance significantly. Results alsoshow that it is possible to get decent predictive values on test data based onlimited amount of training observations. However mix

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Helsene, Adam Paul. "Vertical Data Structures and Computation of Sliding Window Averages in Two-Dimensional Data." Thesis, North Dakota State University, 2020. https://hdl.handle.net/10365/31823.

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A vertical-style data structure and operations on data in that structure are explored and tested in the domain of sliding window average algorithms for geographical information systems (GIS) data. The approach allows working with data of arbitrary precision, which is centrally important for very large GIS data sets. The novel data structure can be constructed from existing multi-channel image data, and data in the structure can be converted back to image data. While in the new structure, operations such as addition, division, and bit-level shifting can be performed in a parallelized manner. I

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Arnroth, Lukas, and Dennis Jonni Fiddler. "Supervised Learning Techniques : A comparison of the Random Forest and the Support Vector Machine." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-274768.

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This thesis examines the performance of the support vector machine and the random forest models in the context of binary classification. The two techniques are compared and the outstanding one is used to construct a final parsimonious model. The data set consists of 33 observations and 89 biomarkers as features with no known dependent variable. The dependent variable is generated through k-means clustering, with a predefined final solution of two clusters. The training of the algorithms is performed using five-fold cross-validation repeated twenty times. The outcome of the training process rev

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Reyaz-Ahmed, Anjum B. "Protein Secondary Structure Prediction Using Support Vector Machines, Nueral Networks and Genetic Algorithms." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cs_theses/43.

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Bioinformatics techniques to protein secondary structure prediction mostly depend on the information available in amino acid sequence. Support vector machines (SVM) have shown strong generalization ability in a number of application areas, including protein structure prediction. In this study, a new sliding window scheme is introduced with multiple windows to form the protein data for training and testing SVM. Orthogonal encoding scheme coupled with BLOSUM62 matrix is used to make the prediction. First the prediction of binary classifiers using multiple windows is compared with single window

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Le, Thu Anh. "An Exploration of the Word2vec Algorithm: Creating a Vector Representation of a Language Vocabulary that Encodes Meaning and Usage Patterns in the Vector Space Structure." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc849728/.

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This thesis is an exloration and exposition of a highly efficient shallow neural network algorithm called word2vec, which was developed by T. Mikolov et al. in order to create vector representations of a language vocabulary such that information about the meaning and usage of the vocabulary words is encoded in the vector space structure. Chapter 1 introduces natural language processing, vector representations of language vocabularies, and the word2vec algorithm. Chapter 2 reviews the basic mathematical theory of deterministic convex optimization. Chapter 3 provides background on some concepts

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Azarmehr, Ramin. "Real-time Embedded Age and Gender Classification in Unconstrained Video." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32463.

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Recently, automatic demographic classification has found its way into embedded applications such as targeted advertising in mobile devices, and in-car warning systems for elderly drivers. In this thesis, we present a complete framework for video-based gender classification and age estimation which can perform accurately on embedded systems in real-time and under unconstrained conditions. We propose a segmental dimensionality reduction technique utilizing Enhanced Discriminant Analysis (EDA) to minimize the memory and computational requirements, and enable the implementation of these classifier

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Nordén, Frans, and Reis Marlevi Filip von. "A Comparative Analysis of Machine Learning Algorithms in Binary Facial Expression Recognition." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254259.

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In this paper an analysis is conducted regarding whether a higher classification accuracy of facial expressions are possible. The approach used is that the seven basic emotional states are combined into a binary classification problem. Five different machine learning algorithms are implemented: Support vector machines, Extreme learning Machine and three different Convolutional Neural Networks (CNN). The utilized CNN:S were one conventional, one based on VGG16 and transfer learning and one based on residual theory known as RESNET50. The experiment was conducted on two datasets, one small contai

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Montagner, Igor dos Santos. "W-operator learning using linear models for both gray-level and binary inputs." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-21082017-111455/.

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Image Processing techniques can be used to solve a broad range of problems, such as medical imaging, document processing and object segmentation. Image operators are usually built by combining basic image operators and tuning their parameters. This requires both experience in Image Processing and trial-and-error to get the best combination of parameters. An alternative approach to design image operators is to estimate them from pairs of training images containing examples of the expected input and their processed versions. By restricting the learned operators to those that are translation inva

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Andersson, Martin, and Marcus Mazouch. "Binary classification for predicting propensity to buy flight tickets. : A study on whether binary classification can be used to predict Scandinavian Airlines customers’ propensity to buy a flight ticket within the next seven days." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160855.

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A customers propensity to buy a certain product is a widely researched field and is applied in multiple industries. In this thesis it is showed that using binary classification on data from Scandinavian Airlines can predict their customers propensity to book a flight within the next coming seven days. A comparison between logistic regression and support vector machine is presented and logistic regression with reduced number of variables is chosen as the final model, due to it’s simplicity and accuracy. The explanatory variables contains exclusively booking history, whilst customer demographics

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Al, Tobi Amjad Mohamed. "Anomaly-based network intrusion detection enhancement by prediction threshold adaptation of binary classification models." Thesis, University of St Andrews, 2018. http://hdl.handle.net/10023/17050.

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Network traffic exhibits a high level of variability over short periods of time. This variability impacts negatively on the performance (accuracy) of anomaly-based network Intrusion Detection Systems (IDS) that are built using predictive models in a batch-learning setup. This thesis investigates how adapting the discriminating threshold of model predictions, specifically to the evaluated traffic, improves the detection rates of these Intrusion Detection models. Specifically, this thesis studied the adaptability features of three well known Machine Learning algorithms: C5.0, Random Forest, and

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Zhao, Xiaochuang. "Ensemble Learning Method on Machine Maintenance Data." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/6056.

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In the industry, a lot of companies are facing the explosion of big data. With this much information stored, companies want to make sense of the data and use it to help them for better decision making, especially for future prediction. A lot of money can be saved and huge revenue can be generated with the power of big data. When building statistical learning models for prediction, companies in the industry are aiming to build models with efficiency and high accuracy. After the learning models have been developed for production, new data will be generated. With the updated data, the models have

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Deaney, Mogammat Waleed. "A Comparison of Machine Learning Techniques for Facial Expression Recognition." University of the Western Cape, 2018. http://hdl.handle.net/11394/6412.

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Magister Scientiae - MSc (Computer Science)<br>A machine translation system that can convert South African Sign Language (SASL) video to audio or text and vice versa would be bene cial to people who use SASL to communicate. Five fundamental parameters are associated with sign language gestures, these are: hand location; hand orientation; hand shape; hand movement and facial expressions. The aim of this research is to recognise facial expressions and to compare both feature descriptors and machine learning techniques. This research used the Design Science Research (DSR) methodology. A DS

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El-Hage, Sebastian. "Predicting Purchase of Airline Seating Using Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280461.

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With the continuing surge in digitalization within the travel industry and the increased demand of personalized services, understanding customer behaviour is becoming a requirement to survive for travel agencies. The number of cases that addresses this problem are increasing and machine learning is expected to be the enabling technique. This thesis will attempt to train two different models, a multi-layer perceptron and a support vector machine, to reliably predict whether a customer will add a seat reservation with their flight booking. The models are trained on a large dataset consisting of

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Kremličková, Lenka. "Hodnocení viability kardiomyocytů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-316800.

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The aim of this diploma thesis is to get acquainted with the properties of image data and the principle of their capture. Literary research on methods of image segmentation in the area of cardiac tissue imaging and, last but not least, efforts to find methods for classification of dead cardiomyocytes and analysis of their viability. Dead cardiomyocytes were analyzed for their shape and similarity to the template created as a mean of dead cells. Another approach was the application of the method based on local binary characters and the computation of symptoms from a simple and associated histog

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Mushfieldt, Diego. "Robust facial expression recognition in the presence of rotation and partial occlusion." Thesis, University of Western Cape, 2014. http://hdl.handle.net/11394/3367.

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>Magister Scientiae - MSc<br>This research proposes an approach to recognizing facial expressions in the presence of rotations and partial occlusions of the face. The research is in the context of automatic machine translation of South African Sign Language (SASL) to English. The proposed method is able to accurately recognize frontal facial images at an average accuracy of 75%. It also achieves a high recognition accuracy of 70% for faces rotated to 60◦. It was also shown that the method is able to continue to recognize facial expressions even in the presence of full occlusions of the e

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Basudhar, Anirban. "Computational Optimal Design and Uncertainty Quantification of Complex Systems Using Explicit Decision Boundaries." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/201491.

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This dissertation presents a sampling-based method that can be used for uncertainty quantification and deterministic or probabilistic optimization. The objective is to simultaneously address several difficulties faced by classical techniques based on response values and their gradients. In particular, this research addresses issues with discontinuous and binary (pass or fail) responses, and multiple failure modes. All methods in this research are developed with the aim of addressing problems that have limited data due to high cost of computation or experiment, e.g. vehicle crashworthiness, flu

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Schäfer, Christian. "Monte Carlo methods for sampling high-dimensional binary vectors." Phd thesis, Université Paris Dauphine - Paris IX, 2012. http://tel.archives-ouvertes.fr/tel-00767163.

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This thesis is concerned with Monte Carlo methods for sampling high-dimensional binary vectors from complex distributions of interest. If the state space is too large for exhaustive enumeration, these methods provide a mean of estimating the expected value with respect to some function of interest. Standard approaches are mostly based on random walk type Markov chain Monte Carlo, where the equilibrium distribution of the chain is the distribution of interest and its ergodic mean converges to the expected value. We propose a novel sampling algorithm based on sequential Monte Carlo methodology w

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Alejos, Marcos. "Transient Expression of BABY BOOM, WUSCHEL, and SHOOT MERISTEMLESS from Virus-Based Vectors in Cotton Explants: Can We Accelerate Somatic Embryogenesis to Improve Transformation Efficiency?" Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1609070/.

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Upland cotton (Gossypium hirsutum L.) is the world's most prominent fiber crop. Cotton transformation is labor intensive and time consuming, taking 12 to 18 months for rooted T0 plants. One rate limiting step is the necessary production of somatic embryos. In other recalcitrant species, ectopic expression of three genes were shown to promote somatic embryogenesis: WUSCHEL (WUS), SHOOT MERISTEMLESS (STM), and BABY BOOM (BBM). WUS is responsible for maintaining stem-cell fate in shoot and floral meristems. STM is needed to establish and maintain shoot meristems. STM and WUS have similar function

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Hutárek, Jiří. "Klasifikace objektů v obraze podle textury." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237277.

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Main subjects of this thesis are texture classification and texture-based object recognition. Various texture features are being explored, including several variants of local binary patterns (LBP). A novel modification of LBP (weighted spatial LBP) is proposed, with intention to improve on the spatial coverage of the traditional LBP. Rarely used color texture features are being discussed as well. Artificial neural networks and support vector machines are used to classify all the aforementioned features. Using these methods, framework for the texture classification and image segmentation is imp

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MURASE, Hiroshi, Kunio KASHINO, Hidehisa NAGANO, 秀尚永野, 邦夫柏野 та 洋. 村瀬. "2値多重音響特徴ベクトルを用いた類似音楽探索とその高速化". 電子情報通信学会, 2003. http://hdl.handle.net/2237/12746.

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Lembke, Benjamin. "Bearing Diagnosis Using Fault Signal Enhancing Teqniques and Data-driven Classification." Thesis, Linköpings universitet, Fordonssystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158240.

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Rolling element bearings are a vital part in many rotating machinery, including vehicles. A defective bearing can be a symptom of other problems in the machinery and is due to a high failure rate. Early detection of bearing defects can therefore help to prevent malfunction which ultimately could lead to a total collapse. The thesis is done in collaboration with Scania that wants a better understanding of how external sensors such as accelerometers, can be used for condition monitoring in their gearboxes. Defective bearings creates vibrations with specific frequencies, known as Bearing Characte

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ROCHA, Simara Vieira da. "Diferenciação do padrão de malignidade e benignidade de massas em imagens de mamografias usando padrões locais binários, geoestatística e índice de diversidade." Universidade Federal do Maranhão, 2014. http://tedebc.ufma.br:8080/jspui/handle/tede/1822.

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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-08-14T19:19:25Z No. of bitstreams: 1 SimaraRocha.pdf: 3984461 bytes, checksum: 04243e2b6ab9b63b0b73e436ebc9fc23 (MD5)<br>Made available in DSpace on 2017-08-14T19:19:25Z (GMT). No. of bitstreams: 1 SimaraRocha.pdf: 3984461 bytes, checksum: 04243e2b6ab9b63b0b73e436ebc9fc23 (MD5) Previous issue date: 2014-05-22<br>Breast cancer is the second most frequent type of cancer in the world, being more common among women, and representing 22% of the new cases every year. A precocious diagnosis improves the chances of a successful treatment.

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Rix, James Gregory. "Hypercube coloring and the structure of binary codes." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2809.

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A coloring of a graph is an assignment of colors to its vertices so that no two adjacent vertices are given the same color. The chromatic number of a graph is the least number of colors needed to color all of its vertices. Graph coloring problems can be applied to many real world applications, such as scheduling and register allocation. Computationally, the decision problem of whether a general graph is m-colorable is NP-complete for m ≥ 3. The graph studied in this thesis is a well-known combinatorial object, the k-dimensional hypercube, Qk. The hypercube itself is 2-colorable for all k; how

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Thiele, Horta Andrés Rodrigo. "Metodología de Clasificación Lineal por Partes: Piecewise Linear Support Vector Machines (PL-SVM)." Tesis, Universidad de Chile, 2011. http://repositorio.uchile.cl/handle/2250/102673.

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El siguiente trabajo de tesis tiene como objetivo plantear una nueva metodología de clasificación binaria que permita obtener resultados predictivos equivalentes a los de los métodos tradicionales, pero salvaguardando caer en el fenómeno de caja negra. Este fenómeno se presenta cuando la técnica de clasificación no entrega interpretabilidad de la forma en que se efectúa la clasificación. El paradigma que se presenta es que, a mayor precisión del método, menor es la interpretabilidad que se obtiene, y viceversa. Una de las técnicas de aprendizaje estadístico con mejores desempeños predict

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Federmann, Christian [Verfasser], and Hans [Akademischer Betreuer] Uszkoreit. "Hybrid machine translation using binary classification models trained on joint, binarised feature vectors / Christian Federmann. Betreuer: Hans Uszkoreit." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2013. http://d-nb.info/1053680112/34.

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Colomer, Granero Adrián. "Fundus image analysis for automatic screening of ophthalmic pathologies." Doctoral thesis, Universitat Politècnica de València, 2018. http://hdl.handle.net/10251/99745.

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En los ultimos años el número de casos de ceguera se ha reducido significativamente. A pesar de este hecho, la Organización Mundial de la Salud estima que un 80% de los casos de pérdida de visión (285 millones en 2010) pueden ser evitados si se diagnostican en sus estadios más tempranos y son tratados de forma efectiva. Para cumplir esta propuesta se pretende que los servicios de atención primaria incluyan un seguimiento oftalmológico de sus pacientes así como fomentar campañas de cribado en centros proclives a reunir personas de alto riesgo. Sin embargo, estas soluciones exigen una alta carga

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Faula, Yannick. "Extraction de caractéristiques sur des images acquises en contexte mobile : Application à la reconnaissance de défauts sur ouvrages d’art." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEI077.

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Le réseau ferroviaire français dispose d’une infrastructure de grande ampleur qui se compose de nombreux ouvrages d’art. Ces derniers subissent les dégradations du temps et du trafic et font donc l’objet d’une surveillance périodique pour détecter l’apparition de défauts. Aujourd’hui, cette inspection se fait en grande partie, visuellement par des opérateurs experts. Plusieurs entreprises testent de nouveaux vecteurs d’acquisition photo comme le drone, destinés à la surveillance des ouvrages de génie civil. Dans cette thèse, l’objectif principal est de développer un système capable de détecter

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Hjelm, Andersson Patrick. "Binär matchning av bilder med hjälp av vektorer från deneuklidiska avståndstransformen." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2440.

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<p>This thesis shows the result from investigations of methods that use distance vectors when matching pictures. The distance vectors are available in a distance map made by the Euclidean Distance Transform. The investigated methods use the two characteristic features of the distance vector when matching pictures, length and direction. The length of the vector is used to calculate a value of how good a match is and the direction of the vector is used to predict a transformation to get a better match. The results shows that the number of calculation steps that are used during a search can be re

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Tissier, Julien. "Improving methods to learn word representations for efficient semantic similarites computations." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSES008.

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De nombreuses applications en traitement du langage naturel (TALN) reposent sur les représentations de mots, ou “word embeddings”. Ces représentations doivent capturer à la fois de l’information syntaxique et sémantique pour donner des bonnes performances dans les tâches en aval qui les utilisent. Cependant, les méthodes courantes pour les apprendre utilisent des textes génériques comme Wikipédia qui ne contiennent pas d’information sémantique précise. De plus, un espace mémoire important est requis pour pouvoir les sauvegarder car le nombre de représentations de mots à apprendre peut être de

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Hussain, Sibt Ul. "Apprentissage machine pour la détection des objets." Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00722632.

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Le but de cette thèse est de développer des méthodes pratiques plus performantes pour la détection d'instances de classes d'objets de la vie quotidienne dans les images. Nous présentons une famille de détecteurs qui incorporent trois types d'indices visuelles performantes - histogrammes de gradients orientés (Histograms of Oriented Gradients, HOG), motifs locaux binaires (Local Binary Patterns, LBP) et motifs locaux ternaires (Local Ternary Patterns, LTP) - dans des méthodes de discrimination efficaces de type machine à vecteur de support latent (Latent SVM), sous deux régimes de réduction de

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Hsu, Chih-Wei, and 許智瑋. "Decomposition Methods for Binary and Multi-class Support Vector Machines." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/18885564730561227819.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>89<br>The decomposition method is currently one of the major methods for solving support vector machines (SVM). An important issue of this method is the selection of working sets. In the first part of this thesis through the design of decomposition methods for bound-constrained SVM formulations and from the experimental analysis we propose a simple selection of the working set which leads to faster convergences for difficul

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Fan, Kuo-Lun, and 范國倫. "Binary Search & Mean Value Predictive Hybrid Fast Vector Quantization Algorithm." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/54042830044642569713.

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碩士<br>立德管理學院<br>應用資訊研究所<br>91<br>Vector Quantization (VQ) is an effective technology for signal compression. In traditional VQ, most of the computation concentrates on searching the nearest codeword in the codebook for each input vector. We propose a fast VQ algorithm to reduce encoding time. There are two main parts in our proposed algorithm. One is pre-processing process and the other is practical encoding process. In pre-processing, we will generate some tables that we need to employ to practical encoding. On the second part, that is a practical encoding and we use the tables that generated

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Wang, Tsung-Chun, and 王宗惇. "Streamflow Prediction Using Support Vector Regression Combined with SOM and Binary Classification." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/tw6ved.

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博士<br>國立臺灣大學<br>土木工程學研究所<br>105<br>The water in Taiwan are is mainly supplied from precipitation. However, the uneven spatial and temporal distribution of rainfall in Taiwan due to the mountainous terrain makes the rainfall difficult to predict. Therefore, it is an important task to make rainfall predictions at different time scales. This study tries to consider a binary classification between rise and decline of flow and then generate the flow predictions using Support Vector Regression (SVR) to improve both the monthly and ten-day flow predictions for five water level stations in Taiwan. Mo

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Valdeavilla, Edreen Bryan Togonon, and 方恩霖. "Classification of Capsule Endoscope Images Using Local Binary Patterns and Support Vector Machines." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/38071942491213912538.

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碩士<br>中原大學<br>電子工程研究所<br>98<br>Wireless capsule endoscopy is the state-of-the-art technology used for the investigation of the large and small intestines. With this technology, a physician can examine the entire section of the intestines, including the blind section not reachable with a traditional endoscope. However, one problem derived from this new technology is the tremendous number of images that need to be inspected visually causing a burden to the physician. This thesis presents some methods for an automatic detection system to reduce this burden by identifying suspected capsule endosco

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Chen, Gang. "Atomistic origins of photo-induced scalar and vector effects in binary semiconducting chalcogenides /." Diss., 2004. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3147314.

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Megahed, Yasmine. "Land cover mapping analysis and urban growth modeling using remote sensing techniques." Master's thesis, 2015. http://hdl.handle.net/10362/14551.

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The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urb

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Uchime, Chidoteremndu Chinonyelum. "Near Sets in Set Pattern Classification." 2015. http://hdl.handle.net/1993/30264.

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This research is focused on the extraction of visual set patterns in digital images, using relational properties like nearness and similarity measures, as well as descriptive properties such as texture, colour and image gradient directions. The problem considered in this thesis is application of topology in visual set pattern discovery, and consequently pattern generation. A visual set pattern is a collection of motif patterns generated from different unique points called seed motifs in the set. Each motif pattern is a descriptive neighbourhood of a seed motif. Such a neighbourhood is a set of

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黃彥穎. "On The Construction of Permutation Arrays via Mappings from Binary Vectors to Permutations." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/06446657071313507664.

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碩士<br>國立交通大學<br>資訊工程系所<br>93<br>In this paper, we continue the study of constructing distance-increasing mappings from binary vectors to permutations. We successfully construct some mappings which induce better lower bounds for permutation codes than the current existing one : P(n,r)>=A(n,r-1). Since the approaches for constructing our mappings are similar, we give a framework for constructing a certain class of mappings. Note that our mappings may not be length-preserving. We will show the necessity of non-length-preserving mappings. We will lose many improvements if we only use length-preser

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Silva, André de Vasconcelos Santos. "Sparse distributed representations as word embeddings for language understanding." Master's thesis, 2018. http://hdl.handle.net/10071/18245.

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Word embeddings are vector representations of words that capture semantic and syntactic similarities between them. Similar words tend to have closer vector representations in a N dimensional space considering, for instance, Euclidean distance between the points associated with the word vector representations in a continuous vector space. This property, makes word embeddings valuable in several Natural Language Processing tasks, from word analogy and similarity evaluation to the more complex text categorization, summarization or translation tasks. Typically state of the art word embedding

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