5 citations · 8 across the 4 of their papers we have counts for
4 papers
Accelerating Multi-Objective Neural Architecture Search by Random-Weight Evaluation
Shengran Hu, Ran Cheng, Cheng He +3
For the goal of automated design of high-performance deep convolutional neural networks (CNNs), Neural Architecture Search (NAS) methodology is becoming increasingly important for…
FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
Shihua Huang, Zhichao Lu, Ran Cheng +1
Recent advancements in deep neural networks have made remarkable leap-forwards in dense image prediction. However, the issue of feature alignment remains as neglected by most exist…
Multi-objective Neural Architecture Search with Almost No Training
Shengran Hu, Ran Cheng, Cheng He +1
In the recent past, neural architecture search (NAS) has attracted increasing attention from both academia and industries. Despite the steady stream of impressive empirical results…
Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs)
Cheng He, Shihua Huang, Ran Cheng +2
Recently, increasing works have proposed to drive evolutionary algorithms using machine learning models. Usually, the performance of such model based evolutionary algorithms is hig…