A Hybrid Gomoku Deep Learning Artificial Intelligence. - Peizhi Yan; Yi Feng (AICCC, 2018)

Using Convolution and Deep Learning in Gomoku Game Artificial Intelligence. - Peizhi Yan; Yi Feng (Parallel Process. Lett., 2018)

A Distributed Graph-Based Dense RFID Readers Arrangement Algorithm. - Peizhi Yan; Salimur Choudhury; Ruizhong Wei (ICC, 2019)

Latency Aware VNF Deployment at Edge Devices for IoT Services: An Artificial Neural Network Based Approach. - Mahzabeen Emu; Peizhi Yan; Salimur Choudhury (ICC Workshops, 2020)

Optimizing Mobile Edge Computing Multi-Level Task Offloading via Deep Reinforcement Learning. - Peizhi Yan; Salimur Choudhury (ICC, 2020)

A Machine Learning Auxiliary Approach for the Distributed Dense RFID Readers Arrangement Algorithm. - Peizhi Yan; Salimur Choudhury; Ruizhong Wei (IEEE Access, 2020)

An energy-efficient topology control algorithm for optimizing the lifetime of wireless ad-hoc IoT networks in 5G and B5G. - Peizhi Yan; Salimur Choudhury; Fadi Al-Turjman 001; Ibrahim Al-Oqily (Comput. Commun., 2020)

Utilizing Deep Learning to Identify Drug Use on Twitter Data. - Joseph Tassone; Peizhi Yan; Mackenzie Simpson; Chetan Harichandra Mendhe; Vijay Mago; Salimur Choudhury (CoRR, 2020)

Utilizing deep learning and graph mining to identify drug use on Twitter data. - Joseph Tassone; Peizhi Yan; Mackenzie Simpson; Chetan Harichandra Mendhe; Vijay Mago; Salimur Choudhury (BMC Medical Informatics Decis. Mak., 2020)

Deep Q-learning enabled joint optimization of mobile edge computing multi-level task offloading. - Peizhi Yan; Salimur Choudhury (Comput. Commun., 2021)

Non-iterative online sequential learning strategy for autoencoder and classifier. - Adhri Nandini Paul; Peizhi Yan; Yimin Yang 001; Hui Zhang 023; Shan Du; Q. M. Jonathan Wu (Neural Comput. Appl., 2021)

NEO-3DF: Novel Editing-Oriented 3D Face Creation and Reconstruction. - Peizhi Yan; James Gregson; Qiang Tang 002; Rabab Ward; Zhan Xu; Shan Du (ACCV (1), 2022)

An Efficient Refocusing Scheme for Camera-Array Captured Light Field Video for Improved Visual Immersiveness. - Nusrat Mehajabin; Peizhi Yan; Supreet Kaur; Jingxiang Song; Mahsa T. Pourazad; Yixiao Wang 001; Hamid Reza Tohidypour; Panos Nasiopoulos (HICSS, 2022)

Network Risk Assessment Method Based on Residual Risk Analysis. - Hao Jing; Peizhi Yan; Gang Wang; Jiewei Liu; Yige Fang (ICIOT, 2022)

Learning Disentangled Features for Nerf-Based Face Reconstruction. - Peizhi Yan; Rabab Ward; Dan Wang 011; Qiang Tang 002; Shan Du (ICIP, 2023)

A Dual-Stage Ensemble Approach to Detect and Classify Ransomware Attacks. - Peizhi Yan; Tala Talaei Khoei; Reena Sajad Hyder; Reemaa Sajad Hyder (UEMCON, 2024)

Artificial neural networks for demand forecasting of the Canadian forest products industry. - Shashi K. Shahi; Peizhi Yan; Salimur Choudhury; Bharat Maheshwari (Int. J. Bus. Inf. Syst., 2024)

Gaussian Déjà-vu: Creating Controllable 3D Gaussian Head-Avatars with Enhanced Generalization and Personalization Abilities. - Peizhi Yan; Rabab Ward; Qiang Tang 002; Shan Du (WACV, 2025)

StyleMorpheus: A Style-Based 3D-Aware Morphable Face Model. - Peizhi Yan; Rabab K. Ward; Dan Wang 011; Qiang Tang 002; Shan Du (CoRR, 2025)