38 citations · 81 across the 6 of their papers we have counts for
6 papers
Adversarial Driving: Attacking End-to-End Autonomous Driving
Han Wu, Syed Yunas, Sareh Rowlands +2
As research in deep neural networks advances, deep convolutional networks become promising for autonomous driving tasks. In particular, there is an emerging trend of employing end-…
Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task
Han Wu, Wenjie Ruan, Jiangtao Wang +8
The black-box nature of machine learning models hinders the deployment of some high-accuracy models in medical diagnosis. It is risky to put one's life in the hands of models that…
CoinMagic: A Differential Privacy Framework for Ring Signature Schemes
Wangze Ni, Han Wu, Peng Cheng +4
By allowing users to obscure their transactions via including "mixins" (chaff coins), ring signature schemes have been widely used to protect a sender's identity of a transaction i…
Can Machine Learn Steganography? - Implementing LSB Substitution and Matrix Coding Steganography with Feed-Forward Neural Networks
Han-Zhou Wu, Hong-Xia Wang, Yun-Qing Shi
In recent years, due to the powerful abilities to deal with highly complex tasks, the artificial neural networks (ANNs) have been studied in the hope of achieving human-like perfor…
Optimal Binary Coding for -state Data Embedding
Han-Zhou Wu
In steganography, we always hope to maximize the embedding payload subject to an upper-bounded distortion. We need suitable distortion measurement to evaluate the embedding impact.…
Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding
Han-Zhou Wu, Hong-Xia Wang, Yun-Qing Shi
This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the s…