Deep Learning Based Multiple Object Detection

Autor:	J Karthika, U Adimulam, M Deepakdharsan, B Akash, H Mohammed Imtiaz
Rok vydání:	2021
Předmět:	History business.industry Computer science Deep learning Computer vision Artificial intelligence business Object detection Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 1916:012225
ISSN:	1742-6596 1742-6588
Popis:	Improvement of automation increases rapidly by deep learning-based object detection. If the small objects are detected by YOLO V3 network, the identification result will not be much successful, so we introduce new technology to find the very small objects by 8X downsampling rate. We modified the YOLO V3 network using LaSOT with the help of anchor values and prediction layer of 4X downsampling layer, this helps to detect very small objects very accurate.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c6197ea4affb7933a9bff8d38707bd4c https://doi.org/10.1088/1742-6596/1916/1/012225 Zobrazit plný text záznamu