li-minn ang

Professor of Electrical & Computer Engineering

University of the Sunshine Coast

Australia

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Li-Minn Ang is a Professor of Electrical & Computer Engineering at the University of the Sunshine Coast, Australia. His research focuses on artificial intelligence and its applications in various fields, including wildfire susceptibility prediction, speech recognition, and smart cities. His recent articles explore advancements in neural networks, distributed learning, and energy optimization in wireless sensor networks.

li-minn ang

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Articles (17)

Benchmarking Artificial Neural Networks and U-Net Convolutional Architectures for Wildfire Susceptibility Prediction: Innovations in Geospatial Intelligence

Collaborative AI Dysarthric Speech Recognition System With Data Augmentation Using Generative Adversarial Neural Network

Customized Binary Convolutional Neural Networks and Neural Architecture Search on Hardware Technologies

Graph Split Federated Learning for Distributed Large-Scale AIoT in Smart Cities

Decentralized and Distributed Learning for AIoT: A Comprehensive Review, Emerging Challenges, and Opportunities

Situation Awareness in AI-Based Technologies and Multimodal Systems: Architectures, Challenges and Applications

CycleGAN*: Collaborative AI Learning With Improved Adversarial Neural Networks for Multimodalities Data

Enf Based Digital Multimedia Forensics: Survey, Application, Challenges And Future Work

An Automated Identification Approach for Partial Discharge Detection Using Density-Based Clustering Without User Inputs

Optimizing Energy Consumption and Provisioning for Wireless Charging & Data Collection in Large-Scale WRSNs with Mobile Elements

Ridesharing and Crowdsourcing for Smart Cities: Technologies, Paradigms and Use Cases

Embedded intelligence and the data-driven future of application-specific Internet of Things for smart environments

Artificial intelligence Internet of Things: A new paradigm of distributed sensor networks

Wireless power transfer and energy harvesting in distributed sensor networks: Survey, opportunities, and challenges

Embedded Intelligence: State-of-the-Art and Research Challenges

Data convexity and parameter independent clustering for biomedical datasets

Embedded Intelligence: Platform Technologies, Device Analytics, and Smart City Applications

Collaborators (2)

Mingzhong Wang

Md Anisur Rahman

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