most citedA class-weighted supervised contrastive learning long-tailed bearing fault diagnosis approach using quadratic neural network

5 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2025

Non-Intrusive Load Monitoring Based on Image Load Signatures and Continual Learning

Olimjon Toirov, Wei Yu

Non-Intrusive Load Monitoring (NILM) identifies the operating status and energy consumption of each electrical device in the circuit by analyzing the electrical signals at the bus,…

eess.SP2023★ 5 cited

A class-weighted supervised contrastive learning long-tailed bearing fault diagnosis approach using quadratic neural network

Wei-En Yu, Jinwei Sun, Shiping Zhang +2

Deep learning has achieved remarkable success in bearing fault diagnosis. However, its performance oftentimes deteriorates when dealing with highly imbalanced or long-tailed data,…