Active Hard Sample Learning for Violation Action Recognition in Power Grid Operation

Active Hard Sample Learning for Violation Action Recognition in Power Grid Operation

Power grid operation occurs in complex, dynamic environments where the timely identification of operator violations is essential for safety. Traditional methods often rely on manual supervision and rule-based detection, leading to inefficiencies. Existing deep learning approaches, while powerful, re...

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Bibliographic Details
Main Authors: Lingwen Meng, Di He, Guobang Ban, Guanghui Xi, Anjun Li, Xinshan Zhu
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Information
Subjects:
violation action recognition
hard sample learning
active learning
semi-supervised learning
power grid operation
Online Access:https://www.mdpi.com/2078-2489/16/1/67
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