Research on Improved Residual Network Classification Method for Defect Recognition of Thermal Battery-Reference-Cited by-同舟云学术

Research on Improved Residual Network Classification Method for Defect Recognition of Thermal Battery

Published:2022 Issue: Volume:10 Page:113234-113248
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Xu Wenchao¹^ORCID,Zhang Sixiang¹,Bai Fang²,Zhao Tao¹

Affiliation:

1. College of Mechanical Engineering, Hebei University of Technology, Tianjin, China

2. College of Information Engineering, Tianjin University of Commerce, Tianjin, China

Funder

Tianjin Education Commission Scientific Research Project: Research on the Development of Collaborative Innovation under the Background of the Integration of Production and Education in Colleges

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09930520.pdf?arnumber=9930520

Reference40 articles.

1. A Study of Defect Detection Techniques for Metallographic Images

2. Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning

3. You Only Look Once: Unified, Real-Time Object Detection

4. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

5. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

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