Faster RCNN for multi-class Foreign Objects detection of Transmission Lines
Author:
Affiliation:
1. State Grid Rizhao Power Supply Company, State Grid Shandong Electric Power,Rizhao,China
2. School of Electrical Engineering, Shandong University,Jinan,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10165685/10164836/10167107.pdf?arnumber=10167107
Reference10 articles.
1. Faster R-CNN for multi-class fruit detection using a robotic vision system
2. DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection
3. A Deep Learning Method to Detect Foreign Objects for Inspecting Power Transmission Lines
4. Traffic signal detection and classification in street views using an attention model;yifan;Computational Visual Media,2018
5. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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1. GEB-YOLO: a novel algorithm for enhanced and efficient detection of foreign objects in power transmission lines;Scientific Reports;2024-07-09
2. Cambodian Multi-Script License Plates Recognition: An Experimental Study;2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA);2023-12-08
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