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Analysis of Feature Extraction Algorithms Based on Deep Learning  

Kim, Gyung Tae (Department of Electronic and Electrical Engineering, Dankook University)
Lee, Yong Hwan (Department of Digital Contents, Wonkwang University)
Kim, Yeong Seop (Department of Electronic and Electrical Engineering, Dankook University)
Publication Information
Journal of the Semiconductor & Display Technology / v.19, no.2, 2020 , pp. 60-67 More about this Journal
Abstract
Recently, artificial intelligence related technologies including machine learning are being applied to various fields, and the demand is also increasing. In particular, with the development of AR, VR, and MR technologies related to image processing, the utilization of computer vision based on deep learning has increased. The algorithms for object recognition and detection based on deep learning required for image processing are diversified and advanced. Accordingly, problems that were difficult to solve with the existing methodology were solved more simply and easily by using deep learning. This paper introduces various deep learning-based object recognition and extraction algorithms used to detect and recognize various objects in an image and analyzes the technologies that attract attention.
Keywords
Deep Learning; Feature Extraction; CNN; RBM;
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