Národní úložiště šedé literatury Nalezeno 2 záznamů.  Hledání trvalo 0.01 vteřin. 
Detection of Material Surface Damage Based on a Photograph
Valko, Marek ; Malaník, Petr (oponent) ; Dyk, Tomáš (vedoucí práce)
This thesis focuses on the detection of surface defects from photograph using computer vision techniques, convolutional neural networks and models for object detection such as Faster R-CNN and YOLO. Different methods of surface damage detection, image processing, neural networks and machine learning are described in detail. The thesis also compares the performance of these models in identification of surface defects on wood and steel using different augmentations of these datasets.
Detekce objektu s využitím hloubkových dat
Valko, Marek ; Hradiš, Michal (oponent) ; Musil, Petr (vedoucí práce)
This bachelor thesis addresses the detection of objects in images using depth data. The goal was to select appropriate deep learning methods and experimentally verify them on relevant datasets. The thesis begins with an overview of basic techniques for detecting objects in images and depth data, utilizing selected datasets NYU Depth v2 and Washington RGB-D to test modified YOLOv5 and YOLOv8 models, adapted for effective processing of RGB-D data. The experiments explored various representations of depth information and analyzed how the integration of depth data enhances the performance of these models. The results demonstrated significant improvements in mAP metrics compared to traditional models that use only RGB data. The integration of depth data thus allowed for more accurate and reliable object detection results.

Viz též: podobná jména autorů
2 Vaľko, Matej
2 Vaľko, Michal
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