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Summary of object detection based on convolutional neural network
Author(s): Xuejiao Wang; Min Zhi
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Paper Abstract

Object detection is one of the most basic and central task in computer vision. Its task is to find all the interested objects in the image, and determine the category and location of the objects. Object detection is widely used and has strong practical value and research prospects. Applications include face detection, pedestrian detection and vehicle detection. In recent years, with the development of convolutional neural network, significant breakthroughs have been made in object detection. This paper describes in detail the classification of object detection algorithms based on deep learning. The algorithms are mainly divided into one-stage object algorithm and two-stage object algorithm, and the general data sets and performance indicators of object detection.

Paper Details

Date Published: 3 January 2020
PDF: 8 pages
Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113730L (3 January 2020); doi: 10.1117/12.2557219
Show Author Affiliations
Xuejiao Wang, Inner Mongolia Normal Univ. (China)
Min Zhi, Inner Mongolia Normal Univ. (China)

Published in SPIE Proceedings Vol. 11373:
Eleventh International Conference on Graphics and Image Processing (ICGIP 2019)
Zhigeng Pan; Xun Wang, Editor(s)

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