Search Results for author: Zihao Liu

Found 8 papers, 3 papers with code

Contrastive and Selective Hidden Embeddings for Medical Image Segmentation

1 code implementation21 Jan 2022 Zhuowei Li, Zihao Liu, Zhiqiang Hu, Qing Xia, Ruiqin Xiong, Shaoting Zhang, Dimitris Metaxas, Tingting Jiang

Medical image segmentation has been widely recognized as a pivot procedure for clinical diagnosis, analysis, and treatment planning.

Contrastive Learning feature selection +2

DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework

no code implementations14 Mar 2018 Zihao Liu, Tao Liu, Wujie Wen, Lei Jiang, Jie Xu, Yanzhi Wang, Gang Quan

To reduce the data storage and transfer overhead in smart resource-limited Internet-of-Thing (IoT) systems, effective data compression is a "must-have" feature before transferring real-time produced dataset for training or classification.

Data Compression General Classification +2

Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples

2 code implementations CVPR 2019 Zihao Liu, Qi Liu, Tao Liu, Nuo Xu, Xue Lin, Yanzhi Wang, Wujie Wen

Image compression-based approaches for defending against the adversarial-example attacks, which threaten the safety use of deep neural networks (DNN), have been investigated recently.

Classification General Classification +2

MT-Spike: A Multilayer Time-based Spiking Neuromorphic Architecture with Temporal Error Backpropagation

no code implementations14 Mar 2018 Tao Liu, Zihao Liu, Fuhong Lin, Yier Jin, Gang Quan, Wujie Wen

Modern deep learning enabled artificial neural networks, such as Deep Neural Network (DNN) and Convolutional Neural Network (CNN), have achieved a series of breaking records on a broad spectrum of recognition applications.

Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks

no code implementations14 Feb 2018 Qi Liu, Tao Liu, Zihao Liu, Yanzhi Wang, Yier Jin, Wujie Wen

In this work, we for the first time investigate the multi-factor adversarial attack problem in practical model optimized deep learning systems by jointly considering the DNN model-reshaping (e. g. HashNet based deep compression) and the input perturbations.

Adversarial Attack

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