Search Results for author: Zhibo Zhang

Found 18 papers, 4 papers with code

Beamforming Optimization for Active RIS-Aided Multiuser Communications With Hardware Impairments

no code implementations16 Feb 2024 Zhangjie Peng, Zhibo Zhang, Cunhua Pan, Marco Di Renzo, Octavia A. Dobre, Jiangzhou Wang

Specifically, by exploiting the majorization-minimization approach, each subproblem is reformulated into a tractable surrogate problem, whose closed-form solutions are obtained by Lagrange dual decomposition approach and element-wise alternating sequential optimization method.

Research on Older Adults' Interaction with E-Health Interface Based on Explainable Artificial Intelligence

no code implementations1 Feb 2024 Xueting Huang, Zhibo Zhang, Fusen Guo, Xianghao Wang, Kun Chi, Kexin Wu

This paper proposed a comprehensive mixed-methods framework with varied samples of older adults, including user experience, usability assessments, and in-depth interviews with the integration of Explainable Artificial Intelligence (XAI) methods.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI)

Reputation-Based Federated Learning Defense to Mitigate Threats in EEG Signal Classification

no code implementations22 Oct 2023 Zhibo Zhang, Pengfei Li, Ahmed Y. Al Hammadi, Fusen Guo, Ernesto Damiani, Chan Yeob Yeun

This paper presents a reputation-based threat mitigation framework that defends potential security threats in electroencephalogram (EEG) signal classification during model aggregation of Federated Learning.

Brain Computer Interface Data Poisoning +5

A Robust Adversary Detection-Deactivation Method for Metaverse-oriented Collaborative Deep Learning

no code implementations21 Oct 2023 Pengfei Li, Zhibo Zhang, Ameena S. Al-Sumaiti, Naoufel Werghi, Chan Yeob Yeun

Metaverse is trending to create a digital circumstance that can transfer the real world to an online platform supported by large quantities of real-time interactions.

Generative Adversarial Network

Explainable Label-flipping Attacks on Human Emotion Assessment System

no code implementations8 Feb 2023 Zhibo Zhang, Ahmed Y. Al Hammadi, Ernesto Damiani, Chan Yeob Yeun

This paper's main goal is to provide an attacker's point of view on data poisoning assaults that use label-flipping during the training phase of systems that use electroencephalogram (EEG) signals to evaluate human emotion.

Data Poisoning EEG +3

Data Poisoning Attacks on EEG Signal-based Risk Assessment Systems

no code implementations8 Feb 2023 Zhibo Zhang, Sani Umar, Ahmed Y. Al Hammadi, Sangyoung Yoon, Ernesto Damiani, Chan Yeob Yeun

Industrial insider risk assessment using electroencephalogram (EEG) signals has consistently attracted a lot of research attention.

Data Poisoning EEG +1

Explainable Data Poison Attacks on Human Emotion Evaluation Systems based on EEG Signals

no code implementations17 Jan 2023 Zhibo Zhang, Sani Umar, Ahmed Y. Al Hammadi, Sangyoung Yoon, Ernesto Damiani, Claudio Agostino Ardagna, Nicola Bena, Chan Yeob Yeun

The major aim of this paper is to explain the data poisoning attacks using label-flipping during the training stage of the electroencephalogram (EEG) signal-based human emotion evaluation systems deploying Machine Learning models from the attackers' perspective.

Data Poisoning EEG +3

A Late Multi-Modal Fusion Model for Detecting Hybrid Spam E-mail

no code implementations26 Oct 2022 Zhibo Zhang, Ernesto Damiani, Hussam Al Hamadi, Chan Yeob Yeun, Fatma Taher

In recent years, spammers are now trying to obfuscate their intents by introducing hybrid spam e-mail combining both image and text parts, which is more challenging to detect in comparison to e-mails containing text or image only.

Optical Character Recognition Optical Character Recognition (OCR)

Person Monitoring by Full Body Tracking in Uniform Crowd Environment

1 code implementation2 Sep 2022 Zhibo Zhang, Omar Alremeithi, Maryam Almheiri, Marwa Albeshr, Xiaoxiong Zhang, Sajid Javed, Naoufel Werghi

The dataset was generated in four different scenarios where mainly the target was moving alongside the crowd, sometimes occluding with them, and other times the camera's view of the target is blocked by the crowd for a short period.

A new database of Houma Alliance Book ancient handwritten characters and classifier fusion approach

no code implementations13 Jul 2022 Xiaoyu Yuan, Zhibo Zhang, Yabo Sun, Zekai Xue, Xiuyan Shao, Xiaohua Huang

This paper proposes a new database of Houma Alliance Book ancient handwritten characters and a multi-modal fusion method to recognize ancient handwritten characters.

TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation

1 code implementation14 Mar 2022 Ruiwen Li, Zheda Mai, Chiheb Trabelsi, Zhibo Zhang, Jongseong Jang, Scott Sanner

In this paper, we propose TransCAM, a Conformer-based solution to WSSS that explicitly leverages the attention weights from the transformer branch of the Conformer to refine the CAM generated from the CNN branch.

Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation

ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification

1 code implementation28 Nov 2021 Zhibo Zhang, Jongseong Jang, Chiheb Trabelsi, Ruiwen Li, Scott Sanner, Yeonjeong Jeong, Dongsub Shim

Contrastive learning has led to substantial improvements in the quality of learned embedding representations for tasks such as image classification.

Adversarial Robustness Classification +2

A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification

no code implementations24 Aug 2018 Wenbin Zhang, Jianwu Wang, Daeho Jin, Lazaros Oreopoulos, Zhibo Zhang

A self-organizing map (SOM) is a type of competitive artificial neural network, which projects the high-dimensional input space of the training samples into a low-dimensional space with the topology relations preserved.

General Classification

Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba

2 code implementations KDD 2018 Jizhe Wang, Pipei Huang, Huan Zhao, Zhibo Zhang, Binqiang Zhao, Dik Lun Lee

Using online A/B test, we show that the online Click-Through-Rate (CTRs) are improved comparing to the previous recommendation methods widely used in Taobao, further demonstrating the effectiveness and feasibility of our proposed methods in Taobao's live production environment.

Graph Embedding Recommendation Systems

Cannot find the paper you are looking for? You can Submit a new open access paper.