Practical application of the YOLO convolutional neural network

• Autorzy: Osuchowski Jakub
• Języki publikacji: EN

Abstrakty

EN

This article presents a practical application of YOLO (You Only Look Once) algorithm. The YOLO convolutional neural network was used for the high voltage line electrical insulator classification and localization purpose. In addition, the article contain a description of YOLO neural network. An important element of the article is comparison of YOLO to others detection systems. A brief review of the YOLO possibilities is also presented.

• Wydawca: Oficyna Wydawnicza Politechniki Opolskiej
• Czasopismo: Zeszyty Naukowe. Elektryka / Politechnika Opolska
• Rocznik: 2019
• Tom: z. 77
• Strony: 83--86
• Opis fizyczny: Bibliogr. 8 poz., rys.

Twórcy

autor

Osuchowski Jakub

• Faculty of Electrical Engineering, Automatic Control and Informatics Institute of Computer Science

Bibliografia

• [1] REDMON J., ANGELOVA A.: Real-Time Grasp Detection Using Convolutional Neural Networks, Computer Vision and Pattern Recognition, 2015
• [2] EHSANI K., BAGHERINEZHAD H., REDMON J., MOTTAGHI R., FARHADI, A.: Who Let The Dogs Out? Modeling Dog Behavior From Visual Data, Computer Vision and Pattern Recognition, 2018
• [3] FELZENSZWALB P.F., GIRSHICK R.B., MCALLESTER D., RAMANAN D.: Object detection with discriminatively trained part based models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
• [4] KRIZHEVSKY A., SUTSKEVER I., HINTON G.E.: Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, 2012
• [5] GIRSHICK R., DONAHUE J., DARRELL T., MALIK J.: Rich feature hierarchies for accurate object detection and semantic segmentation, Computer Vision and Pattern Recognition, 2014
• [6] GIRSHICK R., DONAHUE J., DARRELL T., MALIK J.: Rich feature hierarchies for accurate object detection and semantic segmentation, Computer Vision and Pattern Recognition 2014
• [7] REDMON J., DIVVALA S., GIRSHICK R., FARHADI A.: You Only Look Once : Unified, Real-Time Object Detection, Computer Vision and Pattern Rec., 2016
• [8] REDMON J., FARHADI A.: YOLO9000: Better, Faster, Stronger Joseph, Computer Vision and Pattern Recognition, 2016

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).