Search Results for author: Hui Zhu

Found 13 papers, 4 papers with code

FAS-UNet: A Novel FAS-driven Unet to Learn Variational Image Segmentation

1 code implementation27 Oct 2022 Hui Zhu, Shi Shu, Jianping Zhang

Based on the variational theory and FAS algorithm, we first design a feature extraction sub-network (FAS-Solution module) to solve the model-driven nonlinear systems, where a skip-connection is employed to fuse the multi-scale features.

Image Segmentation Medical Image Segmentation +2

Cross-Skeleton Interaction Graph Aggregation Network for Representation Learning of Mouse Social Behaviour

no code implementations7 Aug 2022 Feixiang Zhou, Xinyu Yang, Fang Chen, Long Chen, Zheheng Jiang, Hui Zhu, Reiko Heckel, Haikuan Wang, Minrui Fei, Huiyu Zhou

Furthermore, we design a novel Interaction-Aware Transformer (IAT) to dynamically learn the graph-level representation of social behaviours and update the node-level representation, guided by our proposed interaction-aware self-attention mechanism.

Representation Learning Self-Supervised Learning

TargetDrop: A Targeted Regularization Method for Convolutional Neural Networks

no code implementations21 Oct 2020 Hui Zhu, Xiaofang Zhao

Dropout regularization has been widely used in deep learning but performs less effective for convolutional neural networks since the spatially correlated features allow dropped information to still flow through the networks.

Mitigating Query-Flooding Parameter Duplication Attack on Regression Models with High-Dimensional Gaussian Mechanism

no code implementations6 Feb 2020 Xiaoguang Li, Hui Li, Haonan Yan, Zelei Cheng, Wenhai Sun, Hui Zhu

Public intelligent services enabled by machine learning algorithms are vulnerable to model extraction attacks that can steal confidential information of the learning models through public queries.

Model extraction regression

Localizing Interpretable Multi-scale informative Patches Derived from Media Classification Task

no code implementations31 Jan 2020 Chuanguang Yang, Zhulin An, Xiaolong Hu, Hui Zhu, Yongjun Xu

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 increased difficult to interpret how relevant patches contribute the final prediction.

General Classification Image Classification

Towards More Efficient and Effective Inference: The Joint Decision of Multi-Participants

no code implementations19 Jan 2020 Hui Zhu, Zhulin An, Kaiqiang Xu, Xiaolong Hu, Yongjun Xu

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 significantly.

DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners

no code implementations20 Nov 2019 Xiaolong Hu, Zhulin An, Chuanguang Yang, Hui Zhu, Kaiqaing Xu, Yongjun Xu

For VGG16 pre-trained on ImageNet, our method averagely gains 14. 29\% accuracy promotion for two-classes sub-tasks.

Rethinking the Number of Channels for the Convolutional Neural Network

no code implementations4 Sep 2019 Hui Zhu, Zhulin An, Chuanguang Yang, Xiaolong Hu, Kaiqiang Xu, Yongjun Xu

In this paper, we propose a method for efficient automatic architecture search which is special to the widths of networks instead of the connections of neural architecture.

Neural Architecture Search

Gated Convolutional Networks with Hybrid Connectivity for Image Classification

1 code implementation26 Aug 2019 Chuanguang Yang, Zhulin An, Hui Zhu, Xiaolong Hu, Kun Zhang, Kaiqiang Xu, Chao Li, Yongjun Xu

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 SMG module, which is augmented by local residual.

Adversarial Defense Classification +2

EENA: Efficient Evolution of Neural Architecture

1 code implementation10 May 2019 Hui Zhu, Zhulin An, Chuanguang Yang, Kaiqiang Xu, Erhu Zhao, Yongjun Xu

Latest algorithms for automatic neural architecture search perform remarkable but are basically directionless in search space and computational expensive in training of every intermediate architecture.

General Classification Neural Architecture Search

Propagation of singularities for gravity-capillary water waves

no code implementations22 Oct 2018 Hui Zhu

To obtain these results, we generalize the paradifferential calculus of Bony to weighted Sobolev spaces and develop a semiclassical paradifferential calculus.

Analysis of PDEs

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