Hsu-Yung Cheng
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View article: Development of the International Classification of Functioning, Disability and Health (ICF) core set for stroke survivors in community-based rehabilitation settings in Hong Kong
Development of the International Classification of Functioning, Disability and Health (ICF) core set for stroke survivors in community-based rehabilitation settings in Hong Kong Open
The final core set reflects key dimensions of functioning relevant to stroke survivors receiving community-based rehabilitation services in Hong Kong.
View article: Enhancing Human Pose Transfer with Convolutional Block Attention Module and Facial Loss Optimization
Enhancing Human Pose Transfer with Convolutional Block Attention Module and Facial Loss Optimization Open
Pose transfer methods often struggle to simultaneously preserve fine-grained clothing textures and facial details, especially under large pose variations. To address these limitations, we propose a model based on the Multi-scale attention …
View article: Pose Transfer with Multi-Scale Features Combined with Latent Diffusion Model and ControlNet
Pose Transfer with Multi-Scale Features Combined with Latent Diffusion Model and ControlNet Open
In recent years, generative AI has become popular in areas like natural language processing, as well as image and audio processing, significantly expanding AI’s creative capabilities. Particularly in the realm of image generation, diffusio…
View article: Feature Weighted Cycle Generative Adversarial Network with Facial Landmark Recognition and Perceptual Color Distance for Enhanced Face Animation Generation
Feature Weighted Cycle Generative Adversarial Network with Facial Landmark Recognition and Perceptual Color Distance for Enhanced Face Animation Generation Open
We propose an anime style transfer model to generate anime faces from human face images. We improve the model by modifying the normalization function to obtain more feature information. To make the face feature position of the anime face s…
View article: Semantic Segmentation of Satellite Images for Landslide Detection Using Foreground-Aware and Multi-Scale Convolutional Attention Mechanism
Semantic Segmentation of Satellite Images for Landslide Detection Using Foreground-Aware and Multi-Scale Convolutional Attention Mechanism Open
Advancements in satellite and aerial imagery technology have made it easier to obtain high-resolution remote sensing images, leading to widespread research and applications in various fields. Remote sensing image semantic segmentation is a…
View article: Enhancing Badminton Game Analysis: An Approach to Shot Refinement via a Fusion of Shuttlecock Tracking and Hit Detection from Monocular Camera
Enhancing Badminton Game Analysis: An Approach to Shot Refinement via a Fusion of Shuttlecock Tracking and Hit Detection from Monocular Camera Open
Extracting the flight trajectory of the shuttlecock in a single turn in badminton games is important for automated sports analytics. This study proposes a novel method to extract shots in badminton games from a monocular camera. First, Tra…
View article: Solar Power Generation Forecast Using Multivariate Convolution Gated Recurrent Unit Network
Solar Power Generation Forecast Using Multivariate Convolution Gated Recurrent Unit Network Open
For the advancement of smart grids, solar power generation predictions have become an important research topic. In the case of using traditional modeling methods, excessive computational costs may be incurred and it is difficult for these …
View article: Incremental Scene Classification Using Dual Knowledge Distillation and Classifier Discrepancy on Natural and Remote Sensing Images
Incremental Scene Classification Using Dual Knowledge Distillation and Classifier Discrepancy on Natural and Remote Sensing Images Open
Conventional deep neural networks face challenges in handling the increasing amount of information in real-world scenarios where it is impractical to gather all the training data at once. Incremental learning, also known as continual learn…
View article: Separable ConvNet Spatiotemporal Mixer for Action Recognition
Separable ConvNet Spatiotemporal Mixer for Action Recognition Open
Video action recognition is vital in the research area of computer vision. In this paper, we develop a novel model, named Separable ConvNet Spatiotemporal Mixer (SCSM). Our goal is to develop an efficient and lightweight action recognition…
View article: Real-Time Object Detection and Tracking for Unmanned Aerial Vehicles Based on Convolutional Neural Networks
Real-Time Object Detection and Tracking for Unmanned Aerial Vehicles Based on Convolutional Neural Networks Open
This paper presents a system applied to unmanned aerial vehicles based on Robot Operating Systems (ROSs). The study addresses the challenges of efficient object detection and real-time target tracking for unmanned aerial vehicles. The syst…
View article: Scene Classification, Data Cleaning, and Comment Summarization for Large-Scale Location Databases
Scene Classification, Data Cleaning, and Comment Summarization for Large-Scale Location Databases Open
This paper presents a framework that can automatically analyze the images and comments in user-uploaded location databases. The proposed framework integrates image processing and natural language processing techniques to perform scene clas…
View article: Applying a Deep Learning Neural Network to Gait-Based Pedestrian Automatic Detection and Recognition
Applying a Deep Learning Neural Network to Gait-Based Pedestrian Automatic Detection and Recognition Open
Gait recognition is a noncontact biometric procedure that determines the identity or health status of a person by analyzing his or her walking posture and habits, including skeletal and joint movements. The most remarkable feature of this …
View article: Generating Scenery Images with Larger Variety According to User Descriptions
Generating Scenery Images with Larger Variety According to User Descriptions Open
In this paper, a framework based on generative adversarial networks is proposed to perform nature-scenery generation according to descriptions from the users. The desired place, time and seasons of the generated scenes can be specified wit…
View article: Radar High-Resolution Range Profile Ship Recognition Using Two-Channel Convolutional Neural Networks Concatenated with Bidirectional Long Short-Term Memory
Radar High-Resolution Range Profile Ship Recognition Using Two-Channel Convolutional Neural Networks Concatenated with Bidirectional Long Short-Term Memory Open
Radar automatic target recognition is a critical research topic in radar signal processing. Radar high-resolution range profiles (HRRPs) describe the radar characteristics of a target, that is, the characteristics of the target that is ref…
View article: Deep Convolutional Neural Network Model for Short-Term Electricity Price Forecasting
Deep Convolutional Neural Network Model for Short-Term Electricity Price Forecasting Open
In the modern power market, electricity trading is an extremely competitive industry. More accurate price forecast is crucial to help electricity producers and traders make better decisions. In this paper, a novel method of convolutional n…
View article: Advanced Driver Assistance Based on Front-View and Rear-Side-View Scene Analysis
Advanced Driver Assistance Based on Front-View and Rear-Side-View Scene Analysis Open
This paper proposes a high-performance advanced driver assistance system that analyses front-view driving scenes and rear-side-view scenes. Dense optical flow analysis is calculated for both views to extract motion information. The system …
View article: Estimating Solar Irradiance on Tilted Surface with Arbitrary Orientations and Tilt Angles
Estimating Solar Irradiance on Tilted Surface with Arbitrary Orientations and Tilt Angles Open
Photovoltaics modules are usually installed with a tilt angle to improve performance and to avoid water or dust accumulation. However, measured irradiance data on inclined surfaces are rarely available, since installing pyranometers with v…
View article: Ego-Lane Position Identification With Event Warning Applications
Ego-Lane Position Identification With Event Warning Applications Open
This paper proposes a high-performance advanced driver assistance system that analyses driving scenes based on monocular cameras. The system identifies the ego-lane position and indicates if the vehicle is driving on an inner or outer lane…
View article: Cloud detection in all-sky images via multi-scale neighborhood features and multiple supervised learning techniques
Cloud detection in all-sky images via multi-scale neighborhood features and multiple supervised learning techniques Open
Cloud detection is important for providing necessary information such as cloud cover in many applications. Existing cloud detection methods include red-to-blue ratio thresholding and other classification-based techniques. In this paper, we…
View article: Cloud Detection in All-Sky Images via Multi-scale Neighborhood Features and Multiple Supervised Learning Techniques
Cloud Detection in All-Sky Images via Multi-scale Neighborhood Features and Multiple Supervised Learning Techniques Open
Cloud detection is important for providing necessary information such as cloud cover in many applications. The classic method for cloud detection is based on thresholding of the red blue ratio of an image pixel. However, it is difficult to…
View article: Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images
Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images Open
In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) a…
View article: Block-based cloud classification with statistical features and distribution of local texture features
Block-based cloud classification with statistical features and distribution of local texture features Open
This work performs cloud classification on all-sky images. To deal with mixed cloud types in one image, we propose performing block division and block-based classification. In addition to classical statistical texture features, the propose…