Pak Kin Wong
YOU?
Author Swipe
View article: Assessing deep learning models for multi-class upper endoscopic disease segmentation: A comprehensive comparative study
Assessing deep learning models for multi-class upper endoscopic disease segmentation: A comprehensive comparative study Open
BACKGROUND Upper gastrointestinal (UGI) diseases present diagnostic challenges during endoscopy due to visual similarities, indistinct boundaries, and observer variability, which can lead to missed diagnoses and delayed treatment. Automate…
View article: An Attention-Driven Multi-Scale Framework for Rotating-Machinery Fault Diagnosis Under Noisy Conditions
An Attention-Driven Multi-Scale Framework for Rotating-Machinery Fault Diagnosis Under Noisy Conditions Open
Failures of rotating machinery, such as bearings and gears, are a critical concern in industrial systems, leading to significant operational downtime and economic losses. A primary research challenge is achieving accurate fault diagnosis u…
View article: Observer-Based Robust Explicit Model Predictive Control for Path Following of Autonomous Electric Vehicles with Communication Delay
Observer-Based Robust Explicit Model Predictive Control for Path Following of Autonomous Electric Vehicles with Communication Delay Open
The existing research on the path following of the autonomous electric vehicle (AEV) mainly focuses on the path planning and the kinematic control. However, the dynamic control with the state observation and the communication delay is usua…
View article: Ultrasound Report Generation with Multimodal Large Language Models for Standardized Texts
Ultrasound Report Generation with Multimodal Large Language Models for Standardized Texts Open
Ultrasound (US) report generation is a challenging task due to the variability of US images, operator dependence, and the need for standardized text. Unlike X-ray and CT, US imaging lacks consistent datasets, making automation difficult. I…
View article: Lane Change Trajectory Planning for Intelligent Electric Vehicles in Dynamic Traffic Environments: Aiming at Optimal Energy Consumption
Lane Change Trajectory Planning for Intelligent Electric Vehicles in Dynamic Traffic Environments: Aiming at Optimal Energy Consumption Open
With the reduction in battery costs and the widespread application of artificial intelligence, the adoption of new-energy vehicles is accelerating. Integrating energy consumption optimization into the process of intelligent development is …
View article: Control-Oriented Modelling and Adaptive Parameter Estimation for Hybrid Wind-Wave Energy Systems
Control-Oriented Modelling and Adaptive Parameter Estimation for Hybrid Wind-Wave Energy Systems Open
Hybrid wind-wave energy system, integrating floating offshore wind turbine and wave energy converters, has received much attention in recent years due to its potential benefit in increasing the power harvest density and reducing the leveli…
View article: Enhancing colorectal polyp classification using gaze-based attention networks
Enhancing colorectal polyp classification using gaze-based attention networks Open
Colorectal polyps are potential precursor lesions of colorectal cancer. Accurate classification of colorectal polyps during endoscopy is crucial for early diagnosis and effective treatment. Automatic and accurate classification of colorect…
View article: Event‐Triggered Anti‐Attack Security Control of Cyber‐Physical Systems With Bio‐Inspired Metaheuristic Algorithm
Event‐Triggered Anti‐Attack Security Control of Cyber‐Physical Systems With Bio‐Inspired Metaheuristic Algorithm Open
This work addresses the event‐triggered anti‐attack security control problem for cyber‐physical systems (CPSs) under denial‐of‐service (DoS) attacks using a bio‐inspired metaheuristic algorithm. First, a fuzzy switching model with the cons…
View article: Control‐Oriented Modelling and Adaptive Parameter Estimation for Hybrid Wind‐Wave Energy Systems
Control‐Oriented Modelling and Adaptive Parameter Estimation for Hybrid Wind‐Wave Energy Systems Open
Hybrid wind‐wave energy systems, integrating floating offshore wind turbine (FOWT) and wave energy converters (WECs), have received much attention in recent years due to its potential benefits in increasing the power harvesting density and…
View article: Broad Critic Deep Actor Reinforcement Learning for Continuous Control
Broad Critic Deep Actor Reinforcement Learning for Continuous Control Open
In the domain of continuous control, deep reinforcement learning (DRL) demonstrates promising results. However, the dependence of DRL on deep neural networks (DNNs) results in the demand for extensive data and increased computational cost.…
View article: Back Propagation Neural Network-Based Fault Diagnosis and Fault Tolerant Control of Distributed Drive Electric Vehicles Based on Sliding Mode Control-Based Direct Yaw Moment Control
Back Propagation Neural Network-Based Fault Diagnosis and Fault Tolerant Control of Distributed Drive Electric Vehicles Based on Sliding Mode Control-Based Direct Yaw Moment Control Open
Distributed-drive vehicles utilize independent drive motors on the four-wheel hubs. The working conditions of the wheel-hub motors are so harsh that the motors are prone to failing under different driving conditions. This study addresses t…
View article: A Novel Electric Motor Fault Diagnosis by Using a Convolutional Neural Network, Normalized Thermal Images and Few-Shot Learning
A Novel Electric Motor Fault Diagnosis by Using a Convolutional Neural Network, Normalized Thermal Images and Few-Shot Learning Open
Motors constitute one critical part of industrial production and everyday life. The effective, timely and convenient diagnosis of motor faults is constantly required to ensure continuous and reliable operations. Infrared imaging technology…
View article: An improved graph convolutional networks for fault diagnosis of rolling bearing with limited labeled data
An improved graph convolutional networks for fault diagnosis of rolling bearing with limited labeled data Open
Rolling bearings are essential parts of rotating equipment. Due to their unique operating environment, bearings are vulnerable to failure. Graph neural network (GNN) provides an effective way of mining relationships between data samples. H…
View article: Semantic Segmentation of Gastric Polyps in Endoscopic Images Based on Convolutional Neural Networks and an Integrated Evaluation Approach
Semantic Segmentation of Gastric Polyps in Endoscopic Images Based on Convolutional Neural Networks and an Integrated Evaluation Approach Open
Convolutional neural networks (CNNs) have received increased attention in endoscopic images due to their outstanding advantages. Clinically, some gastric polyps are related to gastric cancer, and accurate identification and timely removal …
View article: Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview
Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview Open
Gastrointestinal (GI) cancers are the major cause of cancer-related mortality globally. Medical imaging is an important auxiliary means for the diagnosis, assessment and prognostic prediction of GI cancers. Radiomics is an emerging and eff…
View article: Non-fragile robust output feedback control of uncertain activesuspension systems with stochastic network-induced delay
Non-fragile robust output feedback control of uncertain activesuspension systems with stochastic network-induced delay Open
The vehicle active suspension has attracted considerable attention owing to its great contributions to the vertical dynamics of vehicle. This paper investigates the robust non-fragile H ∞ output feedback control problem of the uncertain ve…
View article: Impact of Vehicle Light on Physical Properties of Particulate Matters Emitted from Vehicles
Impact of Vehicle Light on Physical Properties of Particulate Matters Emitted from Vehicles Open
Gasoline and diesel vehicles are one of the main sources of PMs generation which are harmful to human health and the environment. The light emitted from the headlights of these vehicles may cause to make the PMs more/less/not dangerous tha…
View article: Cost-Sensitive Broad Learning System for Imbalanced Classification and Its Medical Application
Cost-Sensitive Broad Learning System for Imbalanced Classification and Its Medical Application Open
As an effective and efficient discriminative learning method, the broad learning system (BLS) has received increasing attention due to its outstanding performance without large computational resources. The standard BLS is derived under the…