Po Yang

Senior Lecturer in Large-scale Data Fusion

University of Sheffield

United Kingdom

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Po Yang is a Senior Lecturer in Large-scale Data Fusion at the University of Sheffield, UK. His research areas include image synthesis and fusion for Alzheimer’s disease diagnosis, federated learning privacy enhancement, spatio-temporal tensor learning for precision agriculture, and multimodal intelligence applications in healthcare. Recent publications reflect his commitment to advancing methodologies in healthcare diagnostics and agricultural technology.

Articles (26)

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2022

Collaborators (10)

Xiyang Peng

University of Sheffield

UNITED KINGDOM

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Chris J. Harris

University of Southampton

UNITED KINGDOM

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Mehmet Mercangöz

Imperial College London

UNITED KINGDOM

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Yuemin Ding

Universidad de Navarra

SPAIN

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Shunbao Li

University of Sheffield

UNITED KINGDOM

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Vitaveska Lanfranchi

University of Sheffield

UNITED KINGDOM

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Fabio Ciravegna

University of Sheffield

UNITED KINGDOM

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Khan Muhammad

Assistant Professor (Tenure-Track)

Sungkyunkwan University

SOUTH KOREA

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Mohammad Hijji

SAUDI ARABIA

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Yunpeng Zhu

Lecturer in Systems Engineering

Queen Mary University of London

UNITED KINGDOM

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Po Yang

Research Interests

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About

Articles (26)

Joint image synthesis and fusion with converted features for Alzheimer’s disease diagnosis

An Interpretable Deep Learning Approach for Alzheimer's Disease Diagnosis Using Gene Expression Data

PEZEGO: A Precision Agriculture System Based on Large Language Models and Internet of Things for Pest Management

Secured Cost-Effective Anonymous Federated Learning With Proxied Privacy Enhancement for Personal Devices

Multi-Scale and Multi-Level Feature Assessment Framework for Classification of Parkinson's Disease State From Short-Term Motor Tasks

Precision Fertilization via Spatio-temporal Tensor Multi-task Learning and One-Shot Learning

Multimodal Wearable Intelligence for Dementia Care in Healthcare 4.0: a Survey

Aphid-YOLO: A Lightweight Detection Model for Real-Time Identification and Counting of Aphids in Complex Field Environments

Unsupervised Transfer Aided Lifelong Regression for Learning New Tasks Without Target Output

Lifelong Learning Meets Dynamic Processes: An Emerging Streaming Process Prediction Framework With Delayed Process Output Measurement

Informative relationship multi-task learning: Exploring pairwise contribution across tasks’ sharing knowledge

Guest Editorial of the Special section on Emerging Technologies and Applications of Consumer Electronics for Healthy and Sustainable Life

Integrating Visualised Automatic Temporal Relation Graph into Multi-Task Learning for Alzheimer's Disease Progression Prediction

Observer-Based Adaptive Finite-Time Neural Control for Constrained Nonlinear Systems With Actuator Saturation Compensation

An effective farmer-centred mobile intelligence solution using lightweight deep learning for integrated wheat pest management

Explainable Tensor Multi-Task Ensemble Learning Based on Brain Structure Variation for Alzheimer’s Disease Dynamic Prediction

Efficient multi-task learning with adaptive temporal structure for progression prediction

Sustainable fertilisation management via tensor multi-task learning using multi-dimensional agricultural data

Efficient adaptive deep gradient RBF network for multi-output nonlinear and nonstationary industrial processes

Privacy-Preserving-Enabled Lightweight COVID-19 Simulation Model for Mobile Intelligent Application

Observer-Based Adaptive Fuzzy Finite-Time Attitude Control for Quadrotor UAVs

A Deep Graph Network with Multiple Similarity for User Clustering in Human–Computer Interaction

Activity graph based convolutional neural network for physical activity recognition using acceleration and gyroscope data

Automatic Detection and Classification System of Domestic Waste via Multimodel Cascaded Convolutional Neural Network

A Multi-classification Accessment Framework for Reproducible Evaluation of Multimodal Learning in Alzheimer's Disease

Controllable Model Compression for Roadside Camera Depth Estimation

Collaborators (10)

Xiyang Peng

Chris J. Harris

Mehmet Mercangöz

Yuemin Ding

Shunbao Li

Vitaveska Lanfranchi

Fabio Ciravegna

Khan Muhammad

Mohammad Hijji

Yunpeng Zhu

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