Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 18 of 18 for “"YOLOv5"”.
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Human Detection for Flood Rescue: Application of YOLOv5 Algorithm and DeepSort Object Tracking
This thesis proposes a method of human detection using high-resolution surveillance cameras to monitor sections of the Chattahoochee River that require frequent search and rescue efforts due to flooding. The areas of interest are located in the city of Columbus, Georgia. The goals of this study are …
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Detekce objektů a sledování trasy pohybu účastníků provozu pro potřeby inteligentních dopravních uzlů
… experiment, který posuzuje detekční modely YOLOv5, YOLOR, Scaled-YOLOv4 a EfficientDet a po- rovnává jejich vlastnosti (rychlost detekce, pamětové nároky, přesnost a jistotu detekce). K tomuto účelu je vytvořena vlastní datová sada, na které jsou tyto parametry zkoumány. Ze studie vyplývá, …
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Skraidančių mikro objektų sekimas /
… different models - Faster R-CNN, YOLOv4 and YOLOv5. These were then trained with the same dataset for drone recognition and compared by the selected metrics - time it took to train them, mAP and recall. Judging by these metrics YOLOv5 achieved the best results and therefore was chosen for the …
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Assessing High Dynamic Range Imagery Performance for Object Detection in Maritime Environments
… of these networks. Faster-RCNN, SSD, and YOLOv5 were used to compare. Results determined Faster-RCNN and YOLOv5 networks trained on fixed exposure images outperformed their HDR counterparts while SSDs performed better when using HDR images. Better fixed exposure network performance is …
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Ally: Designing Interfaces for Human + AI Collaborative Creativity for Computer Aided Design (CAD) Applications
… a Sketch-A-Net model or webcam images using a YOLOv5 model to recognize user input and build a Computer Aided Design (CAD) scene that has been collaboratively created by a human and an algorithm. The devised model is ultimately able to correctly identify the desired part for the user’s design …
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Detekce objektu s využitím hloubkových dat
… RGB-D, na ktorých sa testovali upravené modely YOLOv5 a YOLOv8. Experimenty skúmali rôzne reprezentácie hĺbkových informácií a analyzovali, ako integrácia hĺbkových dát zlepšuje výkon týchto modelov. Výsledky ukázali výrazné zlepšenie metrík mAP pri porovnaní s klasickými modelmi využívajúcimi …
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Les algorithmes d’intelligence artificielle pour la détection, l’inspection des produits naturels : Le bois
… de deux modèles de détection d’objets, YOLOv5 et YOLOv7, directement sur cet ensemble de données en utilisant l’apprentissage par transfert et YOLOv9 pour une base collectée au sein de notre laboratoire. L’évaluation de leurs performances sur des images de test révèle leurs capacités et …
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A distributed multi-vehicle architecture for autonomous driving simulation with an application to autonomous valet parking
… infrastructure-assisted perception through a YOLOv5-based overhead camera module and a multi-vehicle AVP coordination framework for managing shared parking resources. The system enables coordinated vehicle sequencing, exclusive parking spot allocation, and distributed vehicle state …
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Computer Vision Applications in Structural Engineering
… objects. Two candidate deep learning models, Yolov5 and EfficientDet, were compared in their performance. It was found that Yolov5 showed slightly higher mAP performances: Yolov5 models showed mAPs from 87% to 90% and EfficientDet models showed mAPs from 82% to 87%, depending on the complexity …
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Development of an innovative and efficient urban vegetation monitoring system for sustainable urban ecology
… vision systems, this thesis employed the YOLOv5 and YOLOv8 models for automated urban vegetation detection using RGB images from car-mounted cameras. The models were chosen for their effectiveness in image recognition, with various image augmentation techniques and annotation tools …
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Metodologia e plataforma baseadas em aprendizado de máquina para inspeção de defeitos na indústria têxtil
… conducted, comparing eight approaches, including YOLOv5, YOLOv8 variants, and popular networks in the literature, using the TILDA 400 dataset, composed of five distinct defect classes. The YOLOv8 models stood out, especially YOLOv8 medium, which achieved 90.35% accuracy with an inference time of …
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Tracking Human Movement Indoors Using Terrestrial Lidar
… The deep learning approach, specifically the YOLOv5 model, demonstrated high accuracy with an F1 score of 0.879. In contrast, OpenCV methods, while less computationally demanding, showed lower accuracy and higher rates of false detections. Percept, operating on real-time 3D lidar streams, …
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Using machine learning methods to estimate spruce tree crown and DBH from aerial imagery
… that use YOLOs: First method, a combination of YOLOv5 bounding box to identify the trees and watershed technique to segment tree crowns from aerial images. Compared to the second method YOLOv11 that uses instance segmentation to segment the trees. A study is conducted to showcase a relationship …
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Homo prospectus to robo prospectus : towards predictive algorithms for advanced autonomous vehicle perception
… like autonomous racing. By modifying the popular YOLOv5 object detector, the research introduces the `YOLO-Z' series, significantly improving the detection of smaller objects without substantially increasing inference time. This advancement is pivotal for enhancing contextual awareness in AV …
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Automated Rat Grimace Scale for the Assessment of Pain
… for each image. To accomplish this objective, a YOLOv5 object detector and Vision Transformers (ViT) for classification were trained on a dataset of frontal-facing images extracted using Rodent Face Finder®. Subsequently, the model was then validated using a RGS test for blast traumatic brain …
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Supervised and self-supervised deep learning approaches for weed identification and soybean yield prediction
… for weed detection, with YOLOv6 outperforming YOLOv5, attaining an mAP of 81.5% at an average inference speed of 7.05 milliseconds. Self-supervised learning-based yield prediction models reach a coefficient of determination of up to 0.80 and a correlation coefficient of 0.88 between predicted …
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A Study on Deepsea Fish Detection Using Convolutional Neural Networks
… images using approximately 40,000 images. The YOLOv5s model, trained on 4,505 images containing 15,463 bounding-box annotations, achieved a mean average precision (mAP@0.5) of 98.2% All models were trained on the SeaHawk computing cluster with four GPUs. These findings highlight promising …
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Deep learning-based seagrass detection and classification from underwater digital images
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 …