31 citations · 47 across the 4 of their papers we have counts for
4 papers
Reusing Deep Neural Network Models through Model Re-engineering
Binhang Qi, Hailong Sun, Xiang Gao +3
Training deep neural network (DNN) models, which has become an important task in today's software development, is often costly in terms of computational resources and time. With th…
Patching Weak Convolutional Neural Network Models through Modularization and Composition
Binhang Qi, Hailong Sun, Xiang Gao +1
Despite great success in many applications, deep neural networks are not always robust in practice. For instance, a convolutional neuron network (CNN) model for classification task…
Multi-view Feature Augmentation with Adaptive Class Activation Mapping
Xiang Gao, Yingjie Tian, Zhiquan Qi
We propose an end-to-end-trainable feature augmentation module built for image classification that extracts and exploits multi-view local features to boost model performance. Diffe…
Super Resolution Convolutional Neural Network for Feature Extraction in Spectroscopic Data
Han Peng, Xiang Gao, Yu He +8
Two dimensional (2D) peak finding is a common practice in data analysis for physics experiments, which is typically achieved by computing the local derivatives. However, this metho…