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Dissertations / Theses on the topic 'ResNet18'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Saeed, Nausheen. "Automated Gravel Road Condition Assessment : A Case Study of Assessing Loose Gravel using Audio Data." Licentiate thesis, Högskolan Dalarna, Institutionen för information och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-36402.

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Gravel roads connect sparse populations and provide highways for agriculture and the transport of forest goods. Gravel roads are an economical choice where traffic volume is low. In Sweden, 21% of all public roads are state-owned gravel roads, covering over 20,200 km. In addition, there are some 74,000 km of gravel roads and 210,000 km of forest roads that are owned by the private sector. The Swedish Transport Administration (Trafikverket) rates the condition of gravel roads according to the severity of irregularities (e.g. corrugations and potholes), dust, loose gravel, and gravel cross-secti

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Blomqvist, Linus. "Djupinlärning för kameraövervakning." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-40717.

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Allt fler misshandelsbrott sker i Sverige enligt Brå. För att reducera detta kan det som fångats på övervakningskameror användas i brottsutredningar, för att senare användas som bevismaterial till att döma den eller de skyldiga till brottet. Genom att optimera övervakningen kan företag använda sig av automatiserad igenkänning. Automatisering för igenkänningen av normala kontra onormala beteenden går att lösa med djupinlärning. Syftet med denna undersökning är att finna en lämplig modell som kan identifiera det onormala beteendet (till exempel ett slagsmål). Modell arkitekturen som användes und

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3

Bronda, Samuel. "Hluboké neuronové sítě pro prostředí superpočítače." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-400885.

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The main benefit of the work is the optimization of the hardware configuration for the calculation of neural networks. The theoretical part describes neural networks, deep learning frameworks and hardware options. The next part of the thesis deals with implementation of performance tests, which include application of Inception V3 and ResNet models. Network models are applied to various graphics cards and computing hardware. The output of the thesis is the implemented model of the network Inception V3, which examines the graphics cards and their performance, time-consuming calculations and thei

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Vančo, Timotej. "Self-supervised učení v aplikacích počítačového vidění." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442510.

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The aim of the diploma thesis is to make research of the self-supervised learning in computer vision applications, then to choose a suitable test task with an extensive data set, apply self-supervised methods and evaluate. The theoretical part of the work is focused on the description of methods in computer vision, a detailed description of neural and convolution networks and an extensive explanation and division of self-supervised methods. Conclusion of the theoretical part is devoted to practical applications of the Self-supervised methods in practice. The practical part of the diploma thesi

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Nguyen, Thanh Tan. "Selected non-convex optimization problems in machine learning." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/200748/1/Thanh_Nguyen_Thesis.pdf.

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Non-convex optimization is an important and rapidly growing research area. It is tied to the latest success of deep learning, reinforcement learning, matrix factorization, and more. As a contribution to this area, this thesis provides analyses and algorithms for three important problems. The first one is optimization of noisy functions defined on a large graph, which is useful for AB testing, digital marketing. The second one is learning a convex ensemble of basis models, with application in regression and classification. The last one is optimization of ResNet with restricted residual modules,

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D'Amicantonio, Giacomo. "Improvements to knowledge distillation of deep neural networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24178/.

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One of the main problems in the field of Artificial Intelligence is the efficiency of neural networks models. In the past few years, it seemed that most tasks involving such models could simply be solved by designing larger, deeper models and training them on larger datasets for longer time. This approach requires better performing and therefore expensive and energy consuming hardware and will have an increasingly significant environmental impact when those models are deployed at scale. In 2015 G. Hinton, J. Dean and O. Vinyals presented Knowledge Distillation (KD), a technique that leverage

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Kalvakolanu, Anjaneya Teja Sarma. "Brain Tumor Detection and Classification from MRI Images." DigitalCommons@CalPoly, 2021. https://digitalcommons.calpoly.edu/theses/2267.

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A brain tumor is detected and classified by biopsy that is conducted after the brain surgery. Advancement in technology and machine learning techniques could help radiologists in the diagnosis of tumors without any invasive measures. We utilized a deep learning-based approach to detect and classify the tumor into Meningioma, Glioma, Pituitary tumors. We used registration and segmentation-based skull stripping mechanism to remove the skull from the MRI images and the grab cut method to verify whether the skull stripped MRI masks retained the features of the tumor for accurate classification. In

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Asber, Johnny. "A Machine Learning-Based Approach for Fault Detection of Railway Track and its Components." Thesis, Luleå tekniska universitet, Drift, underhåll och akustik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-81275.

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The hard equation of railway safety versus the high commercial profits can only be achieved through the use of new inspection methods supported by modern technologies. The track and its components can have different types of troubles, such as rail surface defects, broken sleepers, missing fasteners, and irregular ballast levels. Each component of the track infrastructure plays a significant role, where the failure or the absence of any of them can pave the way to undesired situations. The rail is designed to carry and direct the train, the sleepers are meant to maintain the level of the rail,

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Zidaoui, Imane. "Advanced data validation methods for wastewater sensors using Artificial Intelligence." Electronic Thesis or Diss., Strasbourg, 2024. http://www.theses.fr/2024STRAD006.

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La fiabilité des données dans la gestion des réseaux d'eaux usées est cruciale en raison des implications directes sur les opérations. Cependant, les approches actuelles de validation des données sont souvent coûteuses et/ou manquent d'objectivité. Cette thèse explore les avancées en intelligence artificielle pour instaurer une validation robuste. La mise en place d'un pôle de validation humaine montre que le F1 score moyen entre experts reste à 0.81, soulignant l'inévitable biais humain. Les modèles testés, à savoir Matrix Profile, ResNet et l'Autoencodeur, présentent des résultats prometteur

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Desai, Gargi Sharad. "Deep Learning for Classification of COVID-19 Pneumonia, Bacterial Pneumonia, Viral Pneumonia and Normal Lungs on CT Images." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627662447914953.

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Frenger, Tobias, and Johan Häggmark. "Transfer learning between domains : Evaluating the usefulness of transfer learning between object classification and audio classification." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-18669.

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Convolutional neural networks have been successfully applied to both object classification and audio classification. The aim of this thesis is to evaluate the degree of how well transfer learning of convolutional neural networks, trained in the object classification domain on large datasets (such as CIFAR-10, and ImageNet), can be applied to the audio classification domain when only a small dataset is available. In this work, four different convolutional neural networks are tested with three configurations of transfer learning against a configuration without transfer learning. This allows for

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Giunchi, Massimiliano. "Reti neurali per la segmentazione di immagini mediche." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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A partire dagli anni '70, con la diffusione dei primi dispositivi per la tomografia assiale computerizzata (TAC), si è assistito ad un'evoluzione sempre più rapida delle modalità con cui si acquisiscono, si conservano e si analizzano le immagini per la diagnosi medica. L’elemento che ha segnato il maggior cambiamento è stato il passaggio da informazioni analogiche, statiche e prettamente bidimensionali come quelle che derivano dalle immagini radiografiche (raggi X), ad informazioni digitali, eventualmente dinamiche e contenenti informazioni tridimensionali. Tutto ciò è stato reso possibile at

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Prax, Jan. "Efektivnost hlubokých konvolučních neuronových sítí na elementární klasifikační úloze." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-442831.

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In this thesis deep convolutional neural networks models and feature descriptor models are compared. Feature descriptors are paired with suitable chosen classifier. These models are a part of machine learning therefore machine learning types are described in this thesis. Further these chosen models are described, and their basics and problems are explained. Hardware and software used for tests is listed and then test results and results summary is listed. Then comparison based on the validation accuracy and training time of these said models is done.

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Cotugno, Giosuè. "Dall’IA all’olio: come affinare i sistemi di classificazione della qualità attraverso tecniche di machine learning con l’utilizzo di reti neurali." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20837/.

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Sino ad oggi, per verificare se un olio è extravergine d’oliva o contiene dei difetti, non abbiamo potuto usufruire di molti supporti tecnologici, infatti la tecnica maggiormente utilizzata per la classificazione degli oli è il panel test che consiste nell’assaggio di questi da un gruppo di persone esperte. Recentemente a seguito di analisi oggettive delle mo- lecole costituenti l’olio, sono state introdotte ulteriori metodologie per la classificazione grazie all’utilizzo di analisi statistiche. Questa tesi, dunque, propone un ulteriore me- todo di classificazione grazie all’utilizzo delle ret

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Darborg, Alex. "Real-time face recognition using one-shot learning : A deep learning and machine learning project." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-40069.

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Face recognition is often described as the process of identifying and verifying people in a photograph by their face. Researchers have recently given this field increased attention, continuously improving the underlying models. The objective of this study is to implement a real-time face recognition system using one-shot learning. “One shot” means learning from one or few training samples. This paper evaluates different methods to solve this problem. Convolutional neural networks are known to require large datasets to reach an acceptable accuracy. This project proposes a method to solve this p

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Vašíčková, Zuzana. "Detekce a hodnocení zkreslených snímků v obrazových sekvencích." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413115.

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Diplomová práca sa zaoberá detekciou a hodnotením skreslených snímok v retinálnych obrazových dátach. Teoretická časť obsahuje stručné zhrnutie anatómie oka a metód hodnotenia kvality obrazov všeobecne, ako aj konkrétne hodnotenie retinálnych obrazov. Praktická časť bola vypracovaná v programovacom jazyku Python. Obsahuje predspracovanie dostupných retinálnych obrazov za účelom vytvorenia vhodného datasetu. Ďalej je navrhnutá metóda hodnotenia troch typov šumu v skreslených retinálnych obrazoch, presnejšie pomocou Inception-ResNet-v2 modelu. Táto metóda nebola prijateľná a navrhnutá bola teda

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Di, Lella Michele Francesco. "Stima della profondità da singola immagine per mezzo di una CNN addestrata mediante tecniche di computer graphics." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13069/.

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In questa tesi viene affrontato il problema della stima della profondità di una scena. Esistono diverse soluzioni a questo problema, come le telecamere stereo, i sensori ad infrarossi, i sensori time-of-flight e i laser scanner 3D. Tutti questi strumenti permettono di stimare più o meno bene la profondità della scena, ma molto spesso sono poco pratici o difficili da utilizzare, e spesso presentano costi molto elevati, e per questi motivi non hanno mai trovato una vera diffusione in ambito commerciale, come invece è successo negli ultimi anni per i dispositivi mobile, come gli smartphone, che h

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Pavlica, Jan. "Re-identifikace graffiti tagů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-432839.

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This thesis focuses on the possibility of using current methods in the field of computer vision to re-identify graffiti tags. The work examines the possibility of using convolutional neural networks to re-identify graffiti tags, which are the most common type of graffiti. The work experimented with various models of convolutional neural networks, the most suitable of which was MobileNet using the triplet loss function, which managed to achieve a mAP of 36.02%.

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Levin, Alexandra, and Najda Vidimlic. "Improving Situational Awareness in Aviation: Robust Vision-Based Detection of Hazardous Objects." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-48568.

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Enhanced vision and object detection could be useful in the aviation domain in situations of bad weather or cluttered environments. In particular, enhanced vision and object detection could improve situational awareness and aid the pilot in environment interpretation and detection of hazardous objects. The fundamental concept of object detection is to interpret what objects are present in an image with the aid of a prediction model or other feature extraction techniques. Constructing a comprehensive data set that can describe the operational environment and be robust for weather and lighting c

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Truzzi, Stefano. "Event classification in MAGIC through Convolutional Neural Networks." Doctoral thesis, Università di Siena, 2022. http://hdl.handle.net/11365/1216295.

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The Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescopes are able to detect gamma rays from the ground with energies beyond several tens of GeV emitted by the most energetic known objects, including Pulsar Wind Nebulae, Active Galactic Nuclei, and Gamma-Ray Bursts. Gamma rays and cosmic rays are detected by imaging the Cherenkov light produced by the charged superluminal leptons in the extended air shower originated when the primary particle interacts with the atmosphere. These Cherenkov flashes brighten the night sky for short times in the nanosecond scale. From the image topology an

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Albert, Florea George, and Filip Weilid. "Deep Learning Models for Human Activity Recognition." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20201.

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AMI Meeting Corpus (AMI) -databasen används för att undersöka igenkännande av gruppaktivitet. AMI Meeting Corpus (AMI) -databasen ger forskare fjärrstyrda möten och naturliga möten i en kontorsmiljö; mötescenario i ett fyra personers stort kontorsrum. För attuppnågruppaktivitetsigenkänninganvändesbildsekvenserfrånvideosoch2-dimensionella audiospektrogram från AMI-databasen. Bildsekvenserna är RGB-färgade bilder och ljudspektrogram har en färgkanal. Bildsekvenserna producerades i batcher så att temporala funktioner kunde utvärderas tillsammans med ljudspektrogrammen. Det har visats att inkluder

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Studená, Zuzana. "Charakterizace chodců ve videu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403159.

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This work deals with obtaining pedestrian information, which are captured by static, external cameras located in public, outdoor or indoor spaces. The aim is to obtain as much information as possible. Information such as gender, age and type of clothing, accessories, fashion style, or overall personality are obtained using using convolutional neural networks. One part of the work consists of creating a new dataset that captures pedestrians and includes information about the person's sex, age, and fashion style. Another part of the thesis is the design and implementation of convolutional neural

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Hagström, Adrian, and Rustam Stanikzai. "Writer identification using semi-supervised GAN and LSR method on offline block characters." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-43316.

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Block characters are often used when filling out forms, for example when writing ones personal number. The question of whether or not there is recoverable, biometric (identity related) information within individual digits of hand written personal numbers is then relevant. This thesis investigates the question by using both handcrafted features and extracting features via Deep learning (DL) models, and successively limiting the amount of available training samples. Some recent works using DL have presented semi-supervised methods using Generative adveserial network (GAN) generated data together

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Galassi, Andrea. "Symbolic versus sub-symbolic approaches: a case study on training Deep Networks to play Nine Men’s Morris game." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/12859/.

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Le reti neurali artificiali, grazie alle nuove tecniche di Deep Learning, hanno completamente rivoluzionato il panorama tecnologico degli ultimi anni, dimostrandosi efficaci in svariati compiti di Intelligenza Artificiale e ambiti affini. Sarebbe quindi interessante analizzare in che modo e in quale misura le deep network possano sostituire le IA simboliche. Dopo gli impressionanti risultati ottenuti nel gioco del Go, come caso di studio è stato scelto il gioco del Mulino, un gioco da tavolo largamente diffuso e ampiamente studiato. È stato quindi creato il sistema completamente sub-simbolico

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WANG, FU-CHING, and 王富慶. "Tire Bubble Defects Detection Using ResNet." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/ph97y5.

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碩士<br>國立雲林科技大學<br>資訊工程系<br>107<br>Digital shearography used to detect tire bubble defects that are unobservable by the naked-eye. The tire manufacturer obtains the tire image through digital shearography, and then judges the bubble defect through the experience operate. The determination of the bubble defects depends not only on the experience and observation of the personnel, but also because there is no uniform judgment standard due to different personnel. This thesis proposes a residual network to detect bubble defects. In the training phase, the whole tire image is divided into several blo

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Yang, Chi-Hsin, and 楊啟昕. "(High Accuracy Text Detection and Recognition using ResNet as Feature Extraction." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/ry38j8.

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碩士<br>大同大學<br>資訊工程學系(所)<br>107<br>In passed decades, a complete procedure in Optical Character Recognition (OCR) has established. The procedure is mainly split into three parts: text detection, text recognition, and post-processing. In fact, traditional OCR system cannot handle scene text. Text detection in natural scene images is much more difficult than the recognition of text in scanned document images because of its complicating background. Moreover, Chinese character detection and recognition are difficult topic in OCR due to its numerous characters. Popular existing methods for character

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Lin, He-Kuan, and 林和寬. "Classified Fatty Livers of Abdominal Ultrasound Tomography by Using Nested ResNet Method." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3cvxa4.

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碩士<br>義守大學<br>資訊工程學系<br>107<br>In clinics, the diagnosis of fatty liver via ultrasound images is subjectively. Meanwhile, Computer-Aided Diagnosis (CAD) was adopted to classify stages of fatty liver through manually pre-processing and extracting features of images. Now a day, the artificial intelligent with deep learning algorithms are developed to identify or classify the categories of image. In this study, the ResNet, performed with small sample, was utilized to classify the stages of fatty liver. A retrospective designed with multiple groups were enrolled in this study. The liver ultrasound

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Huang, Zih-Syuan, and 黃梓玹. "Analyzing Image Quality of Abdominal Ultrasound Tomography Using Logistic Regression and ResNet50 Approaches: A Phantom Study." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/r7s47h.

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碩士<br>義守大學<br>資訊工程學系<br>107<br>In clinics, the quality of ultrasound image is usually subjective determination. So far, the quality of ultrasound image is not clearly defined proper criteria. In this study, ResNet50 approach and logistic regression model were used to classify the quality of ultrasound images. The SonoSite 180+ and curve probe with frequency 2-5 MHz were used to be imaging instruments. Experimental ultrasound images were obtained from a human abdominal prosthesis (E-130328-368T). The locations of imaging were along with epigastric region. The organs were including liver, gallbl

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Jian-ShiunWu and 吳建勳. "Integration of Siamese Network and ResNet Models for Cross-view Localization of UAV." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/cm2fxa.

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Hsiao, Sheng-Hsing, and 蕭勝興. "Improving ResNet-based Feature Extractor for Face Recognition via Re-ranking and Approximate Nearest Neighbor Search." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/xe855p.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>107<br>Deep residual network (ResNet) is one of the state-of-the-art architectures in image classification and object detection, which can serve as a robust feature extractor when the last layer is removed. Once the faces are embedded as feature vectors, tasks such as face recognition, verification and identification can be easily implemented using some distance measurements. This paper proposes a framework for face recognition based on feature extractor from ResNet, together with other steps for improving its performance, including face detection, face alignment, f

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Xuan-PingZhou and 周軒平. "Automatic Multi-Drug Detection based on Enhanced Feature Pyramid Networks and Inception-ResNet-based Drug Classification System." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/m6p9j4.

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Mirzaei, Muhammad Ehsan. "Impact evaluation of skin color, gender, and hair on the performance of eigenface, ICA, and, CNN methods." Master's thesis, 2020. http://hdl.handle.net/10362/104578.

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Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence<br>Although face recognition has made remarkable progress in the past decades, it is still a challenging area. In addition to traditional flaws (such as illumination, pose, occlusion in part of face image), the low performance of the system with dark skin images and female faces raises questions that challenge transparency and accountability of the system. Recent work has suggested that available datasets are causing this

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Bukar, Ali M., and Hassan Ugail. "On automatic age estimation from facial profile view." 2017. http://hdl.handle.net/10454/13041.

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Yes<br>In recent years, automatic facial age estimation has gained popularity due to its numerous applications. Much work has been done on frontal images and lately, minimal estimation errors have been achieved on most of the benchmark databases. However, in reality, images obtained in unconstrained environments are not always frontal. For instance, when conducting a demographic study or crowd analysis, one may get profile images of the face. To the best of our knowledge, no attempt has been made to estimate ages from the side-view of face images. Here we exploit this by using a pre-trained de

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Inácio, Ana Rita da Silva. "Selecção de áreas prioritárias para a conservação da biodiversidade no sul de Portugal." Master's thesis, 2004. http://hdl.handle.net/10400.1/1641.

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Dissertação de mest., Gestão e Conservação da Natureza, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2004<br>A selecção de áreas prioritárias para a conservação da biodiversidade no Sudoeste Serrano e Baixo Guadiana é o primeiro objectivo de qualquer plano de conservação para esta região. A ausência de informação sistemática e completa sobre a biodiversidade existente conduziu à utilização de indicadores de biodiversidade (10 comunidades vegetais, 58 espécies de flora e 21 de fauna), bem como a utilização de modelos de regressão logística. O programa ResNet permiti

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Martins, Cecília Eduarda Coelho Machado da Cruz. "Machine learning and image processing." Master's thesis, 2020. http://hdl.handle.net/1822/73671.

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Dissertação de mestrado em Matemática e Computação<br>Portuguese legislation states the compulsory reporting of the addition of amenities, such as swimming pools, to the Portuguese tax authority. The purpose is to update the property tax value, to be charged annually to the owner of each real estate. According to Technavio and Market- Watch, this decade will bring a global rise to the number of swimming pools due to certain factors such as: cost reduction, increasing health consciousness, and others. The need for inspections to ensure that all new constructions are communicated to the com

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Albuquerque, Carina Isabel Andrade. "Convolutional neural networks for cell detection and counting : a case study of human cell quantification in zebrafish xenografts using deep learning object detection techniques." Master's thesis, 2019. http://hdl.handle.net/10362/62425.

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Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>Deep learninghad,inrecentyears,becamethestateofthearttodealwithcomputer vision problems.Onthecomputervisionresearchfield,objectdetectionisatechnique thatallowstolocalizeandclassifyoneormoreobjectsinaninputimage.Thisapproach can beappliedtoseveraltasksandproblems,ascellcountinginmedicalimaging,as proposed inthisthesis. Cellcountingisafrequentlyneededtaskinseveralmedicaltypesofresearch,butof- ten stillmademanuallyduetoseveralconstraints.Theautomationofthisprocesscan

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Santos, Felipe Vieira dos. "Aprendizado profundo aplicado no monitoramento de insetos em culturas de citros." Master's thesis, 2018. http://hdl.handle.net/10198/22839.

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Recentemente, detectou-se em Portugal, o inseto Trioza erytrea, o qual tem a possibilidade de transmitir a doença Huanglongbing (Citrus Greening) prejudicial à cultura dos citrinos. Esta patologia ainda não possui cura e tem alto potencial lesivo ao cultivo. Embora a doença não se manifestou-se em território português, métodos preventivos, baseados no monitoramento da quantidade de Triozas, são indispensáveis para efetivas estratégias de contingência, assim como antecipar uma possível disseminação. O método tradicional de monitoramento é realizado por intermédio de um profissional incumb

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