Journal of Computer and Communications

Volume 10, Issue 1 (January 2022)

ISSN Print: 2327-5219   ISSN Online: 2327-5227

Google-based Impact Factor: 1.12  Citations  

Overview of Object Detection Algorithms Using Convolutional Neural Networks

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DOI: 10.4236/jcc.2022.101006    1,192 Downloads   12,157 Views  Citations
Author(s)

ABSTRACT

In today’s world, computer vision technology has become a very important direction in the field of Internet applications. As one of the basic problems of computer vision, object detection has become the basis of many vision tasks. Whether we need to realize the interaction between images and text or recognize fine categories, it provides reliable information. This article reviews the development of object detection networks. Starting from RCNN, we introduce object detection based on candidate regions, including Fast R-CNN, Faster R-CNN, etc.; and then start to introduce single-shot networks including YOLO, SSD, and Retina Net, etc. Detectors are the most excellent methods at present. By reviewing the current research status of object detection networks, it provides suggestions for the further development trend and research of object detection.

Share and Cite:

Ren, J. and Wang, Y. (2022) Overview of Object Detection Algorithms Using Convolutional Neural Networks. Journal of Computer and Communications, 10, 115-132. doi: 10.4236/jcc.2022.101006.

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