4 citations · 5 across the 4 of their papers we have counts for
4 papers
Energy-Efficient Prediction in Textile Manufacturing: Enhancing Accuracy and Data Efficiency With Ensemble Deep Transfer Learning
Yan-Chen Chen, Wei-Yu Chiu, Qun-Yu Wang +2
Traditional textile factories consume substantial energy, making energy-efficient production optimization crucial for sustainability and cost reduction. Meanwhile, deep neural netw…
Active Learning for Multiple Change Point Detection in Non-stationary Time Series with Deep Gaussian Processes
Hao Zhao, Rong Pan
Multiple change point (MCP) detection in non-stationary time series is challenging due to the variety of underlying patterns. To address these challenges, we propose a novel algori…
Gaussian Derivative Change-point Detection for Early Warnings of Industrial System Failures
Hao Zhao, Rong Pan
An early warning of future system failure is essential for conducting predictive maintenance and enhancing system availability. This paper introduces a three-step framework for ass…
Active Learning for Abrupt Shifts Change-point Detection via Derivative-Aware Gaussian Processes
Hao Zhao, Rong Pan
Change-point detection (CPD) is crucial for identifying abrupt shifts in data, which influence decision-making and efficient resource allocation across various domains. To address…