Sai Ho Ling

Senior Lecturer

University of Sydney

Australia

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About

Sai Ho Ling is a Senior Lecturer at the University of Technology Sydney, Australia. His research focuses on advanced techniques in medical imaging, brain-computer interfaces, and deep learning applications, as evidenced by his recent publications. He has contributed to the development of hybrid models for ultrasound image segmentation, signal processing in BCIs, and automated assessments of neurological symptoms.

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Collaborators (5)

Ananda Sanagavarapu

Associate Professor

University of Sydney

AUSTRALIA

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Chin Moi Chow

Associate Professor

University of Sydney

AUSTRALIA

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Juan M. Gorriz

Visiting Professor

University of Cambridge

UNITED KINGDOM

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Quang Ha

Associate Professor

University of Sydney

AUSTRALIA

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Peter Plapper

LUXEMBOURG

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Sai Ho Ling

Research Interests

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About

Articles (22)

A Improved Hybrid Attention Recurrent Residual U-Net approach for the segmentation of ultrasound spine images

Evolving optimized transformer-hybrid systems for robust BCI signal processing using genetic algorithms

Voice-Based Assessment of Extrapyramidal Symptoms Using Deep Learning

Multimodal learning for non-small cell lung cancer prognosis

MUF-Net: A Novel Self-Attention Based Dual-Task Learning Approach for Automatic Left Ventricle Segmentation in Echocardiography

DCONet: A Dual-Task Collaborative Optimization Network for Infrared Small Target Detection

Stability Analysis of Dynamic General Type-2 Fuzzy Control System With Uncertainty

Exploring the frontier: Transformer-based models in EEG signal analysis for brain-computer interfaces

Next-Gen Medical Imaging: U-Net Evolution and the Rise of Transformers

Development of real-time brain-computer interface control system for robot

Landmark Localization From Medical Images With Generative Distribution Prior

EEG-TCNTransformer: A Temporal Convolutional Transformer for Motor Imagery Brain–Computer Interfaces

Advancing Fault Detection in HVAC Systems: Unifying Gramian Angular Field and 2D Deep Convolutional Neural Networks for Enhanced Performance

Multi-classification for EEG motor imagery signals using data evaluation-based auto-selected regularized FBCSP and convolutional neural network

Design of Confidence-Integrated Denoising Auto-Encoder for Personalized Top-N Recommender Systems

Intrabody Molecular Communication via Blood-Tissue Barrier for Internet of Bio-Nano Things

A generalized algorithm for the automatic diagnosis of sleep apnea from per-sample encoding of airflow and oximetry

Modified SqueezeNet Architecture for Parkinson’s Disease Detection Based on Keypress Data

Sleep Apnea Detection Using Multi-Error-Reduction Classification System with Multiple Bio-Signals

Joint Spine Segmentation and Noise Removal From Ultrasound Volume Projection Images With Selective Feature Sharing

Evolving Optimised Convolutional Neural Networks for Lung Cancer Classification

Auto-Denoising for EEG Signals Using Generative Adversarial Network

Collaborators (5)

Ananda Sanagavarapu

Chin Moi Chow

Juan M. Gorriz

Quang Ha

Peter Plapper

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