no code implementations • 4 Feb 2024 • Brian Etter, James Lee Hu, Mohammedreza Ebrahimi, Weifeng Li, Xin Li, Hsinchun Chen
Adversarial Malware Generation (AMG), the gen- eration of adversarial malware variants to strengthen Deep Learning (DL)-based malware detectors has emerged as a crucial tool in the development of proactive cyberdefense.
no code implementations • 18 Nov 2023 • Zhenrong Wang, Bin Li, Weifeng Li, Shuanlong Niu, Wang Miao, Tongzhi Niu
Deep convolutional neural networks (CNNs) have been widely used in surface defect detection.
no code implementations • 25 Jan 2023 • Tongzhi Niu, Bin Li, Kai Li, Yufeng Lin, Yuwei Li, Weifeng Li, Zhenrong Wang
In the surface defect detection, there are some suspicious regions that cannot be uniquely classified as abnormal or normal.
no code implementations • 25 Oct 2022 • James Lee Hu, MohammadReza Ebrahimi, Weifeng Li, Xin Li, Hsinchun Chen
This provides an opportunity for the defenders (i. e., malware detectors) to detect the adversarial variants by utilizing more than one view of a malware file (e. g., source code view in addition to the binary view).
1 code implementation • 27 Jun 2022 • Zechen Wang, Liangzhen Zheng, Sheng Wang, Mingzhi Lin, Zhihao Wang, Adams Wai-Kin Kong, Yuguang Mu, Yanjie Wei, Weifeng Li
In this work, we propose a fully differentiable framework for ligand pose optimization based on a hybrid scoring function (SF) combined with a multi-layer perceptron (DeepRMSD) and the traditional AutoDock Vina SF.
no code implementations • 8 Jan 2022 • Ning Zhang, MohammadReza Ebrahimi, Weifeng Li, Hsinchun Chen
In this study, we propose a novel framework for automated breaking of dark web CAPTCHA to facilitate dark web data collection.
no code implementations • 11 Nov 2021 • Yizhi Liu, Fang Yu Lin, MohammadReza Ebrahimi, Weifeng Li, Hsinchun Chen
While Information Extraction (IE) techniques can be used to extract the PII automatically, Deep Learning (DL)-based IE models alleviate the need for feature engineering and further improve the efficiency.
1 code implementation • 22 Mar 2021 • Zechen Wang, Liangzhen Zheng, Yang Liu, Yuanyuan Qu, Yong-Qiang Li, Mingwen Zhao, Yuguang Mu, Weifeng Li
In this study, we proposed a simple scoring function (called OnionNet-2) based on convolutional neural network to predict $\triangle$$G$.
no code implementations • 11 Mar 2021 • Yanmei Yang, Yunju Zhang, Yuanyuan Qu, Xuewei Liu, Mingwen Zhao, Yuguang Mu, Weifeng Li
Energy decomposition analyses identified three binding patches in the SARS-CoV-2 RBD and eleven key residues (Phe486, Tyr505, Asn501, Tyr489, Gln493, Leu455 and etc) which are believed to be the main targets for drug development.
no code implementations • 23 Sep 2013 • Xin Zheng, Zhiyong Wu, Helen Meng, Weifeng Li, Lianhong Cai
In this paper, we first present a new variant of Gaussian restricted Boltzmann machine (GRBM) called multivariate Gaussian restricted Boltzmann machine (MGRBM), with its definition and learning algorithm.