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Dissertations / Theses on the topic 'YOLOv10'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Oškera, Jan. "Detekce dopravních značek a semaforů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-432850.

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The thesis focuses on modern methods of traffic sign detection and traffic lights detection directly in traffic and with use of back analysis. The main subject is convolutional neural networks (CNN). The solution is using convolutional neural networks of YOLO type. The main goal of this thesis is to achieve the greatest possible optimization of speed and accuracy of models. Examines suitable datasets. A number of datasets are used for training and testing. These are composed of real and synthetic data sets. For training and testing, the data were preprocessed using the Yolo mark tool. The trai

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Borngrund, Carl. "Machine vision for automation of earth-moving machines : Transfer learning experiments with YOLOv3." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-75169.

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This master thesis investigates the possibility to create a machine vision solution for the automation of earth-moving machines. This research was done as without some type of vision system it will not be possible to create a fully autonomous earth moving machine that can safely be used around humans or other machines. Cameras were used as the primary sensors as they are cheap, provide high resolution and is the type of sensor that most closely mimic the human vision system. The purpose of this master thesis was to use existing real time object detectors together with transfer learning and exa

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Melcherson, Tim. "Image Augmentation to Create Lower Quality Images for Training a YOLOv4 Object Detection Model." Thesis, Uppsala universitet, Signaler och system, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-429146.

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Research in the Arctic is of ever growing importance, and modern technology is used in news ways to map and understand this very complex region and how it is effected by climate change. Here, animals and vegetation are tightly coupled with their environment in a fragile ecosystem, and when the environment undergo rapid changes it risks damaging these ecosystems severely. Understanding what kind of data that has potential to be used in artificial intelligence, can be of importance as many research stations have data archives from decades of work in the Arctic. In this thesis, a YOLOv4 object d

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Norling, Samuel. "Tree species classification with YOLOv3 : Classification of Silver Birch (Betula pendula) and Scots Pine (Pinus sylvestris)." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260244.

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Automation of tree species classification during a forest inventory could potentially provide more efficiency and better results for forest companies and stakeholding agencies. This thesis investigates how well a state of the art object detection system, YOLOv3, performs this classification task. A new image dataset with pictures of Silver Birches and Scots Pines, called LilljanNet, was created to train YOLOv3. After training YOLOv3 on half the dataset we performed validation by testing it against the other half. The trained model scored a mean average precision above 0.99. Training was also d

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Ståhl, Sebastian. "A tracking framework for a dynamic non- stationary environment." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288955.

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As the use of unmanned aerial vehicles (UAVs) increases in popularity across the globe, their fields of application are constantly growing. This thesis researches the possibility of using a UAV to detect, track, and geolocate a target in a dynamic nonstationary environment as the seas. In this case, different projection and apparent size of the target in the captured images can lead to ambiguous assignments of coordinated. In this thesis, a framework based on a UAV, a monocular camera, a GPS receiver, and the UAV’s inertial measurement unit (IMU) is developed to perform the task of detecting,

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Ye, Fanjie. "A Method of Combining GANs to Improve the Accuracy of Object Detection on Autonomous Vehicles." Thesis, University of North Texas, 2020. https://digital.library.unt.edu/ark:/67531/metadc1752364/.

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As the technology in the field of computer vision becomes more and more mature, the autonomous vehicles have achieved rapid developments in recent years. However, the object detection and classification tasks of autonomous vehicles which are based on cameras may face problems when the vehicle is driving at a relatively high speed. One is that the camera will collect blurred photos when driving at high speed which may affect the accuracy of deep neural networks. The other is that small objects far away from the vehicle are difficult to be recognized by networks. In this paper, we present a meth

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Wang, Chen. "2D object detection and semantic segmentation in the Carla simulator." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-291337.

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The subject of self-driving car technology has drawn growing interest in recent years. Many companies, such as Baidu and Tesla, have already introduced automatic driving techniques in their newest cars when driving in a specific area. However, there are still many challenges ahead toward fully autonomous driving cars. Tesla has caused several severe accidents when using autonomous driving functions, which makes the public doubt self-driving car technology. Therefore, it is necessary to use the simulator environment to help verify and perfect algorithms for the perception, planning, and decisio

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Kharel, Subash. "POTHOLE DETECTION USING DEEP LEARNING AND AREA ASSESSMENT USING IMAGE MANIPULATION." OpenSIUC, 2021. https://opensiuc.lib.siu.edu/theses/2825.

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Every year, drivers are spending over 3 billions to repair damage on vehicle caused by potholes. Along with the financial disaster, potholes cause frustration in drivers. Also, with the emerging development of automated vehicles, road safety with automation in mind is being a necessity. Deep Learning techniques offer intelligent alternatives to reduce the loss caused by spotting pothole. The world is connected in such a way that the information can be shared in no time. Using the power of connectivity, we can communicate the information of potholes to other vehicles and also the department of

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Roohi, Masood. "end-point detection of a deformable linear object from visual data." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21133/.

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In the context of industrial robotics, manipulating rigid objects have been studied quite deeply. However, Handling deformable objects is still a big challenge. Moreover, due to new techniques introduced in the object detection literature, employing visual data is getting more and more popular between researchers. This thesis studies how to exploit visual data for detecting the end-point of a deformable linear object. A deep learning model is trained to perform the task of object detection. First of all, basics of the neural networks is studied to get more familiar with the mechanism of the ob

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Svedberg, Malin. "Analys av inskannade arkiverade dokument med hjälp av objektdetektering uppbyggt på AI." Thesis, Högskolan i Gävle, Avdelningen för datavetenskap och samhällsbyggnad, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-32612.

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Runt om i världen finns det en stor mängd historiska dokument som endast finns i pappersform. Genom att digitalisera dessa dokument förenklas bland annat förvaring och spridning av dokumenten. Vid digitalisering av dokument räcker det oftast inte att enbart skanna in dokumenten och förvara dem som en bild, oftast finns det önskemål att kunna hantera informationen som dokumenten innehåller på olika vis. Det kan t.ex. vara att söka efter en viss information eller att sortera dokumenten utifrån informationen dem innehåller. Det finns olika sätt att digitalisera dokument och extrahera den informat

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Yesudasu, Santheep. "Cοntributiοn à la manipulatiοn de cοlis sοus cοntraintes par un tοrse humanοïde : applicatiοn à la dépaléttisatiοn autοnοme dans les entrepôts lοgistiques". Electronic Thesis or Diss., Normandie, 2024. https://theses.hal.science/tel-04874770.

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Cette thèse de doctorat explore le développement et l'implémentation d'URNik-AI, un système de dépalettisation automatisé basé sur l'intelligence artificielle (IA), conçu pour manipuler des boîtes en carton de tailles et de poids variés à l'aide d'un torse humanoïde à double bras. L'objectif principal est d'améliorer l'efficacité, la précision et la fiabilité des tâches de dépalettisation industrielle grâce à l'intégration de la robotique avancée, de la vision par ordinateur et des techniques d'apprentissage profond.Le système URNik-AI est composé de deux bras robotiques UR10 équipés de capteu

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Hasanaj, Enis, Albert Aveler, and William Söder. "Cooperative edge deepfake detection." Thesis, Jönköping University, JTH, Avdelningen för datateknik och informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53790.

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Deepfakes are an emerging problem in social media and for celebrities and political profiles, it can be devastating to their reputation if the technology ends up in the wrong hands. Creating deepfakes is becoming increasingly easy. Attempts have been made at detecting whether a face in an image is real or not but training these machine learning models can be a very time-consuming process. This research proposes a solution to training deepfake detection models cooperatively on the edge. This is done in order to evaluate if the training process, among other things, can be made more efficient wit

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Mikulský, Petr. "Detekce pohybujících se objektů ve videu s využitím neuronových sítí." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442377.

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This diploma thesis deals with the detection of moving objects in a video recording using neural networks. The aim of the thesis was to detect road users in video recordings. Pre-trained YOLOv5 object detection model was used for a practical part of the thesis. As part of the solution, an own dataset of traffic road video recordings was created and annotated with following classes: a car, a bus, a van, a motorcycle, a truck and a trailer truck. Final version of this dataset comprise 5404 frames and 6467 annotated objects in total. After training, the YOLOv5 model achieved 0.995 mAP, 0.995 prec

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Noman, Md Kislu. "Deep learning-based seagrass detection and classification from underwater digital images." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2023. https://ro.ecu.edu.au/theses/2648.

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Deep learning is the most popular branch of machine learning and has achieved great success in many real-life applications. Deep learning algorithms, in particular Convolutional Neural Networks (CNNs), have rapidly become a method of choice for analysing seagrass image data. Deep learning-based seagrass classification and detection are very challenging due to the limited labelled data, intraclass similarities between species, lighting conditions, and complex shapes and structures in the underwater environment, which make them different from large-scale dataset objects. The light propagating th

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Uhrín, Peter. "Počítání unikátních aut ve snímcích." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445493.

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Current systems for counting cars on parking lots usually use specialized equipment, such as barriers at the parking lot entrance. Usage of such equipment is not suitable for free or residential parking areas. However, even in these car parks, it can help keep track of their occupancy and other data. The system designed in this thesis uses the YOLOv4 model for visual detection of cars in photos. It then calculates an embedding vector for each vehicle, which is used to describe cars and compare whether the car has changed over time at the same parking spot. This information is stored in the dat

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Jacobzon, Gustaf. "Multi-site Organ Detection in CT Images using Deep Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279290.

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When optimizing a controlled dose in radiotherapy, high resolution spatial information about healthy organs in close proximity to the malignant cells are necessary in order to mitigate dispersion into these organs-at-risk. This information can be provided by deep volumetric segmentation networks, such as 3D U-Net. However, due to limitations of memory in modern graphical processing units, it is not feasible to train a volumetric segmentation network on full image volumes and subsampling the volume gives a too coarse segmentation. An alternative is to sample a region of interest from the image

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Ali, Hani, and Pontus Sunnergren. "Scenanalys - Övervakning och modellering." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-45036.

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Självkörande fordon kan minska trafikstockningar och minska antalet trafikrelaterade olyckor. Då det i framtiden kommer att finnas miljontals autonoma fordon krävs en bättre förståelse av omgivningen. Syftet med detta projekt är att skapa ett externt automatiskt trafikledningssystem som kan upptäcka och spåra 3D-objekt i en komplex trafiksituation för att senare skicka beteendet från dessa objekt till ett större projekt som hanterar med att 3D-modellera trafiksituationen. Projektet använder sig av Tensorflow ramverket och YOLOv3 algoritmen. Projektet använder sig även av en kamera för att spel

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Charvát, Michal. "System for People Detection and Localization Using Thermal Imaging Cameras." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-432478.

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V dnešním světě je neustále se zvyšující poptávka po spolehlivých automatizovaných mechanismech pro detekci a lokalizaci osob pro různé účely -- od analýzy pohybu návštěvníků v muzeích přes ovládání chytrých domovů až po hlídání nebezpečných oblastí, jimiž jsou například nástupiště vlakových stanic. Představujeme metodu detekce a lokalizace osob s pomocí nízkonákladových termálních kamer FLIR Lepton 3.5 a malých počítačů Raspberry Pi 3B+. Tento projekt, navazující na předchozí bakalářský projekt "Detekce lidí v místnosti za použití nízkonákladové termální kamery", nově podporuje modelování kom

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Lavado, Diana Martins. "Sorting Surgical Tools from a Clustered Tray - Object Detection and Occlusion Reasoning." Master's thesis, 2018. http://hdl.handle.net/10316/86257.

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Trabalho de Projeto do Mestrado Integrado em Engenharia Biomédica apresentado à Faculdade de Ciências e Tecnologia<br>O principal objetivo desta dissertação de mestrado é classificar e localizar os instrumentos cirúrgicos presentes numa bandeja desorganizada, assim como realizar o raciocínio para resolver oclusão por forma a determinar qual o instrumento que deverá ser retirado em primeiro lugar. Estas tarefas pretendem ser uma parte integrante de um sistema complexo apto a separar instrumentos cirúrgicos após a sua desinfeção, de modo a montar kits cirúrgicos e, esperançosamente, otimizar o t

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CHEN, WEI-LUN, and 陳威倫. "Downsized-YOLOv3 for SAR Imagery Ship Detection." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/535hpk.

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碩士<br>國立臺北科技大學<br>電機工程系<br>107<br>Synthetic aperture radar (SAR) is a radar with superior traversal. The radar emits energy, then get the reflects after reaches the surface. Compared with visible light, it can easily penetrate the clouds and is not affected by climate conditions. SAR has a wide range of object detection and monitoring, and produce high-resolution images, also has been widely used in aviation and spacecraft. This study obtained the ship and oil spill dataset(SOSD) and SAR ship detection dataset(SSDD). We enhanced the training samples to improve the detection accuracy. These two

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Min-ZhiJi and 紀旻志. "Optimization of YOLOv3 Inference Engine for Edge Device." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/7kj82c.

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碩士<br>國立成功大學<br>電機工程學系<br>107<br>For neural networks used in low-end edge devices, there are several approaches to dealing with, such that compressing model, quantifying model and designing hardware accelerators. However, the number of parameters of the current NN (neural network) models is increasing, and the current NN frameworks typically initialize the entire NN model in the initial stage. So, memory requirement will be very huge. In order to reduce memory requirement, we propose layer-wise memory management based on Darknet. But NN models maybe have complex network structures with residua

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LIAO, YI-CHIEN, and 廖宜健. "The Real-Time Pedestrian Detection with YOLOv3-Reduce." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/axd9mn.

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碩士<br>國立臺北科技大學<br>電機工程系<br>107<br>In recent years, with the energetically of computer vision, there are many different ways to create architectures in the field of object detection. Among them, the deep learning neural network architecture is the mainstream. This study uses the deep learning method to perform pedestrian detection in object detection, and uses the COCO (Common Objects in Context) database provided by Microsoft for training and evaluation. The deep learning method optimizes the YOLOv3 (You Only Look Once version 3) architecture, detects the target object, and tests and evaluates

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Liao, Szu-Yu, and 廖思羽. "Implementing 3D Semantic Maps by Visual SLAM Integrated with YOLOv3." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5441095%22.&searchmode=basic.

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碩士<br>國立中興大學<br>電機工程學系所<br>107<br>In recent years, Simultaneous Localization And Mapping (SLAM) becomes an important topic in the research area of unmanned vehicles. The sensors adopted by SLAM are mainly divided into lidar and camera approaches. A camera is cost-efficeint and easy to obtain. Thus it is extensively used in implementing SLAM. Particularly, ORB-SLAM2 is a real-time visual SLAM method based on feature points, supporting high-precision three-dimensional (3D) maps with monocular cameras, stereo cameras, and RGB-D cameras. However, it is unable to assign semantic labels to objects o

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(8786558), Mehul Nanda. "You Only Gesture Once (YouGo): American Sign Language Translation using YOLOv3." Thesis, 2020.

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<div>The study focused on creating and proposing a model that could accurately and precisely predict the occurrence of an American Sign Language gesture for an alphabet in the English Language</div><div>using the You Only Look Once (YOLOv3) Algorithm. The training dataset used for this study was custom created and was further divided into clusters based on the uniqueness of the ASL sign.</div><div>Three diverse clusters were created. Each cluster was trained with the network known as darknet. Testing was conducted using images and videos for fully trained models of each cluster and</div><div>A

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Lee, Felix, and 李宏德. "The real-time pedestrian detection by embedded GPU with YOLOv3-mobile." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/7x69h5.

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碩士<br>國立臺北科技大學<br>電機工程系<br>106<br>Pedestrian detection technology is widely used throughout the industry, especially in the field of self-driving cars development. To ensure that the process of driving pedestrians safety and accurately determine the relative position of pedestrians is the crucial part to build a reliable and robust self-driving car. In the future, it can be also through IoT (Internet of things ) to do remote traffic monitoring. Recently the DNNs (deep neural networks) have been demonstrated to be superior to other approaches for object detection in terms of performance and ac

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YIN, I.-CHENG, and 印翊誠. "UAV Images Overlapping Regions Candidates based on YOLOv3 with Traditional Feature Matching." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/63797d.

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碩士<br>國立臺北科技大學<br>電機工程系<br>107<br>Due to Unmanned Aerial Vehicle can use the methods such as remote control, automatic flight, etc. to performs a specific mission, and it also can be equipped with sensing equipment to perform the mission of environment investigations, so it gradually become to one of the main tools of the aerial mapping in the recently years. This paper will candidates the overlapping regions on UAV images based on the deep learning method, in order to save more times on feature detector and feature matching of two full size adjacent images, it assist in pending timely image s

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Phong-PhuLe and 黎楓富. "Ball-Grid-Array Chip Defects Detection and Classification Using Patch-based Modified YOLOv3." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/vyywa9.

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Wei-ChungTseng and 曾微中. "Layer-wise Fixed Point Quantization for Deep Convolutional Neural Networks and Implementation of YOLOv3 Inference Engine." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/x46nq6.

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碩士<br>國立成功大學<br>電腦與通信工程研究所<br>107<br>With the increasing popularity of mobile devices and the effectiveness of deep learning-based algorithms, people try to put deep learning models on mobile devices. However, it is limited by the complexity of computational and software overhead. We propose an efficient framework for inference to fit resource-limited devices with about 1000 times smaller than Tensorflow in code size, and a layer-wised quantization scheme that allows inference computed by fixed-point arithmetic. The fixed-point quantization scheme is more efficient than floating point arithmet

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Троян, Дмитро Віталійович. "Комп’ютерна система керування роботом для збору тенісних м’ячів". Магістерська робота, 2021. https://dspace.znu.edu.ua/jspui/handle/12345/5702.

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Троян Д. В. Комп’ютерна система керування роботом для збору тенісних м’ячів : кваліфікаційна робота магістра спеціальності 121 «Інженерія програмного забезпечення» / наук. керівник В. Г. Вербицький. Запоріжжя : ЗНУ, 2021. 96 с.<br>UA : Об’єкт дослідження – сукупність складових ІТ, що забезпечує роботоздатність системи - це навігація, фізика руху і нейронна мережа для розпізнавання об'єктів. Завданням науково-дослідницької роботи є дослідження можливостей використання технології для реалізації системи керування роботом для збору тенісних м’ячиків на корті. Задача також вимагає використання ней

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Velosa, José Filipe Góis. "Classification and processing of marine Images." Master's thesis, 2019. http://hdl.handle.net/10400.13/2662.

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