Efficient sampling-based energy function evaluation for ensemble optimization using simulated annealing
作者：
Highlights：
• A sampling-based evaluation method is proposed for accelerating optimization with simulated annealing over large image datasets.
• The sampling strategy is constructed using convergence results for noisy evaluation.
• The proposed method significantly reduces the time requirement of the optimization while preserves convergence in probability to the global optimum.
• As an application, an ensemble for diabetic retinopathy pre-screening is created and optimized.
摘要
•A sampling-based evaluation method is proposed for accelerating optimization with simulated annealing over large image datasets.•The sampling strategy is constructed using convergence results for noisy evaluation.•The proposed method significantly reduces the time requirement of the optimization while preserves convergence in probability to the global optimum.•As an application, an ensemble for diabetic retinopathy pre-screening is created and optimized.
论文关键词：Diabetic retinopathy,Ensemble,Microaneurysm detection,Parameter optimization,Sampling-based evaluation,Simulated annealing
论文评审过程：Received 8 October 2019, Revised 26 May 2020, Accepted 17 June 2020, Available online 19 June 2020, Version of Record 25 June 2020.
论文官网地址：https://doi.org/10.1016/j.patcog.2020.107510
