77 citations · 219 across the 17 of their papers we have counts for
19 papers
GlassesGB: Controllable 2D GAN-Based Eyewear Personalization for 3D Gaussian Blendshapes Head Avatars
Rui-Yang Ju, Jen-Shiun Chiang
Virtual try-on systems allow users to interactively try different products within VR scenarios. However, most existing VTON methods operate only on predefined eyewear templates and…
MFE-GAN: Efficient GAN-based Framework for Document Image Enhancement and Binarization with Multi-scale Feature Extraction
Rui-Yang Ju, KokSheik Wong, Yanlin Jin +1
Document image enhancement and binarization are commonly performed prior to document analysis and recognition tasks for improving the efficiency and accuracy of optical character r…
DKDS: A Benchmark Dataset of Degraded Kuzushiji Documents with Seals for Detection and Binarization
Rui-Yang Ju, Kohei Yamashita, Hirotaka Kameko +1
Kuzushiji, a pre-modern Japanese cursive script, can currently be read and understood by only a few thousand trained experts in Japan. With the rapid development of deep learning,…
ToonifyGB: StyleGAN-based Gaussian Blendshapes for 3D Stylized Head Avatars
Rui-Yang Ju, Sheng-Yen Huang, Yi-Ping Hung
The introduction of 3D Gaussian blendshapes has enabled the real-time reconstruction of animatable head avatars from monocular video. Toonify, a StyleGAN-based method, has become w…
Pediatric Wrist Fracture Detection Using Feature Context Excitation Modules in X-ray Images
Rui-Yang Ju, Chun-Tse Chien, Enkaer Xieerke +1
Children often suffer wrist trauma in daily life, while they usually need radiologists to analyze and interpret X-ray images before surgical treatment by surgeons. The development…
YOLOv8-ResCBAM: YOLOv8 Based on An Effective Attention Module for Pediatric Wrist Fracture Detection
Rui-Yang Ju, Chun-Tse Chien, Jen-Shiun Chiang
Wrist trauma and even fractures occur frequently in daily life, particularly among children who account for a significant proportion of fracture cases. Before performing surgery, s…
ORB-SfMLearner: ORB-Guided Self-supervised Visual Odometry with Selective Online Adaptation
Yanlin Jin, Rui-Yang Ju, Haojun Liu +1
Deep visual odometry, despite extensive research, still faces limitations in accuracy and generalizability that prevent its broader application. To address these challenges, we pro…
Global Context Modeling in YOLOv8 for Pediatric Wrist Fracture Detection
Rui-Yang Ju, Chun-Tse Chien, Chia-Min Lin +1
Children often suffer wrist injuries in daily life, while fracture injuring radiologists usually need to analyze and interpret X-ray images before surgical treatment by surgeons. T…
Efficient Generative Adversarial Networks for Color Document Image Enhancement and Binarization Using Multi-scale Feature Extraction
Rui-Yang Ju, KokSheik Wong, Jen-Shiun Chiang
The outcome of text recognition for degraded color documents is often unsatisfactory due to interference from various contaminants. To extract information more efficiently for text…
YOLOv9 for Fracture Detection in Pediatric Wrist Trauma X-ray Images
Chun-Tse Chien, Rui-Yang Ju, Kuang-Yi Chou +1
The introduction of YOLOv9, the latest version of the You Only Look Once (YOLO) series, has led to its widespread adoption across various scenarios. This paper is the first to appl…
YOLOv8-AM: YOLOv8 Based on Effective Attention Mechanisms for Pediatric Wrist Fracture Detection
Chun-Tse Chien, Rui-Yang Ju, Kuang-Yi Chou +2
Wrist trauma and even fractures occur frequently in daily life, particularly among children who account for a significant proportion of fracture cases. Before performing surgery, s…
CCDWT-GAN: Generative Adversarial Networks Based on Color Channel Using Discrete Wavelet Transform for Document Image Binarization
Rui-Yang Ju, Yu-Shian Lin, Jen-Shiun Chiang +3
To efficiently extract textual information from color degraded document images is a significant research area. The prolonged imperfect preservation of ancient documents has led to…
Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy
Rui-Yang Ju, Chih-Chia Chen, Jen-Shiun Chiang +3
The Transformer-based method has demonstrated remarkable performance for image super-resolution in comparison to the method based on the convolutional neural networks (CNNs). Howev…
Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks
Rui-Yang Ju, Yu-Shian Lin, Yanlin Jin +3
The efficient extraction of text information from the background in degraded color document images is an important challenge in the preservation of ancient manuscripts. The imperfe…
Connection Reduction of DenseNet for Image Recognition
Rui-Yang Ju, Jen-Shiun Chiang, Chih-Chia Chen +1
Convolutional Neural Networks (CNN) increase depth by stacking convolutional layers, and deeper network models perform better in image recognition. Empirical research shows that si…
Efficient Convolutional Neural Networks on Raspberry Pi for Image Classification
Rui-Yang Ju, Ting-Yu Lin, Jia-Hao Jian +1
With the good performance of deep learning algorithms in the field of computer vision (CV), the convolutional neural network (CNN) architecture has become a main backbone of the co…
Aggregated Pyramid Vision Transformer: Split-transform-merge Strategy for Image Recognition without Convolutions
Rui-Yang Ju, Ting-Yu Lin, Jen-Shiun Chiang +3
With the achievements of Transformer in the field of natural language processing, the encoder-decoder and the attention mechanism in Transformer have been applied to computer visio…
ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce Connections
Rui-Yang Ju, Ting-Yu Lin, Jia-Hao Jian +2
With the continuous development of neural networks for computer vision tasks, more and more network architectures have achieved outstanding success. As one of the most advanced neu…
New Pruning Method Based on DenseNet Network for Image Classification
Rui-Yang Ju, Ting-Yu Lin, Jen-Shiun Chiang
Deep neural networks have made significant progress in the field of computer vision. Recent studies have shown that depth, width and shortcut connections of neural network architec…