National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Detection of Weapons in 2D Image
Demčák, Ján ; Spurný, Martin (referee) ; Drahanský, Martin (advisor)
This bachelor thesis deals with detection of weapons in 2D image. In the theoretical part of the thesis the term weapon was defined and the possibilities of detection of weapons in image with using classic methods and deep neural networks were mentioned there. The key steps of image processing, objects classification and detection were described. The overview of frameworks, libraries was presented. To implement the pratical part of the thesis, 3 models were chosen. The first classic model with using HOG transformation. The second CNN model with priority target detection accuracy and with two different neural network architectures as classifiers. The third model with YOLO network architecture had as priority target real-time detection. The essential part of each model was choice, or more precisely creating suitable dataset. What followed was the construction and implementation of models and the evaluation of obtained data.
Detection of Weapons in 2D Image
Demčák, Ján ; Spurný, Martin (referee) ; Drahanský, Martin (advisor)
This bachelor thesis deals with detection of weapons in 2D image. In the theoretical part of the thesis the term weapon was defined and the possibilities of detection of weapons in image with using classic methods and deep neural networks were mentioned there. The key steps of image processing, objects classification and detection were described. The overview of frameworks, libraries was presented. To implement the pratical part of the thesis, 3 models were chosen. The first classic model with using HOG transformation. The second CNN model with priority target detection accuracy and with two different neural network architectures as classifiers. The third model with YOLO network architecture had as priority target real-time detection. The essential part of each model was choice, or more precisely creating suitable dataset. What followed was the construction and implementation of models and the evaluation of obtained data.

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