4 citations · 5 across the 3 of their papers we have counts for
7 papers
Localizing Interpretable Multi-scale informative Patches Derived from Media Classification Task
Chuanguang Yang, Zhulin An, Xiaolong Hu +2
Deep convolutional neural networks (CNN) always depend on wider receptive field (RF) and more complex non-linearity to achieve state-of-the-art performance, while suffering the inc…
Towards More Efficient and Effective Inference: The Joint Decision of Multi-Participants
Hui Zhu, Zhulin An, Kaiqiang Xu +2
Existing approaches to improve the performances of convolutional neural networks by optimizing the local architectures or deepening the networks tend to increase the size of models…
DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners
Xiaolong Hu, Zhulin An, Chuanguang Yang +3
Convolutional neural networks (ConvNets) are widely used in real life. People usually use ConvNets which pre-trained on a fixed number of classes. However, for different applicatio…
Rethinking the Number of Channels for the Convolutional Neural Network
Hui Zhu, Zhulin An, Chuanguang Yang +3
Latest algorithms for automatic neural architecture search perform remarkable but few of them can effectively design the number of channels for convolutional neural networks and co…
Gated Convolutional Networks with Hybrid Connectivity for Image Classification
Chuanguang Yang, Zhulin An, Hui Zhu +5
We propose a simple yet effective method to reduce the redundancy of DenseNet by substantially decreasing the number of stacked modules by replacing the original bottleneck by our…
Multi-Objective Pruning for CNNs Using Genetic Algorithm
Chuanguang Yang, Zhulin An, Chao Li +2
In this work, we propose a heuristic genetic algorithm (GA) for pruning convolutional neural networks (CNNs) according to the multi-objective trade-off among error, computation and…