2 citations · 3 across the 2 of their papers we have counts for
2 papers
eess.IV2023★ 2 cited
BiGSeT: Binary Mask-Guided Separation Training for DNN-based Hyperspectral Anomaly Detection
Haijun Liu, Xi Su, Xiangfei Shen +2
Hyperspectral anomaly detection (HAD) aims to recognize a minority of anomalies that are spectrally different from their surrounding background without prior knowledge. Deep neural…
cs.CV2023★ 1 cited
Resource Efficient Neural Networks Using Hessian Based Pruning
Jack Chong, Manas Gupta, Lihui Chen
Neural network pruning is a practical way for reducing the size of trained models and the number of floating-point operations. One way of pruning is to use the relative Hessian tra…