Research Article
Multi-object Detection by Using CNN for Power Transmission Line Inspection
@INPROCEEDINGS{10.1007/978-3-030-77424-0_28, author={Dinh Cong Nguyen and The Cuong Nguyen and Dinh Hung Phan and Nhan Tam Le and Van Vien Tran}, title={Multi-object Detection by Using CNN for Power Transmission Line Inspection}, proceedings={Industrial Networks and Intelligent Systems. 7th EAI International Conference, INISCOM 2021, Hanoi, Vietnam, April 22-23, 2021, Proceedings}, proceedings_a={INISCOM}, year={2021}, month={5}, keywords={Power transmission inspection Multi-object detection Aerial image}, doi={10.1007/978-3-030-77424-0_28} }- Dinh Cong Nguyen
The Cuong Nguyen
Dinh Hung Phan
Nhan Tam Le
Van Vien Tran
Year: 2021
Multi-object Detection by Using CNN for Power Transmission Line Inspection
INISCOM
Springer
DOI: 10.1007/978-3-030-77424-0_28
Abstract
Multi-object detection for power transmission line is one of the key tasks to control and monitor quality of the system. In the past, defective objects were found out by naked-eye inspection through aerial images and relied on the experienced workers. Due to harsh environmental conditions, manual observation might be a time-consuming and dangerous task. Recently, this task has been supported by machine learning where deep-learning algorithms are applied to increase the efficiency of detection/recognition phases. This paper discusses different approaches for multi-object detection based on Convolutional Neural Network (CNN) model to investigate the quality and condition of power lines in Vietnam. Our proposed system outperforms the state-of-the-art methods on our dataset.
