47 citations · 66 across the 11 of their papers we have counts for
11 papers
A Closer Look at Geometric Temporal Dynamics for Face Anti-Spoofing
Chih-Jung Chang, Yaw-Chern Lee, Shih-Hsuan Yao +4
Face anti-spoofing (FAS) is indispensable for a face recognition system. Many texture-driven countermeasures were developed against presentation attacks (PAs), but the performance…
Streamlined Framework for Agile Forecasting Model Development towards Efficient Inventory Management
Jonathan Hans Soeseno, Sergio González, Trista Pei-Chun Chen
This paper proposes a framework for developing forecasting models by streamlining the connections between core components of the developmental process. The proposed framework enabl…
Kinship Representation Learning with Face Componential Relation
Weng-Tai Su, Min-Hung Chen, Chien-Yi Wang +2
Kinship recognition aims to determine whether the subjects in two facial images are kin or non-kin, which is an emerging and challenging problem. However, most previous methods foc…
Development of a deep learning-based tool to assist wound classification
Po-Hsuan Huang, Yi-Hsiang Pan, Ying-Sheng Luo +4
This paper presents a deep learning-based wound classification tool that can assist medical personnel in non-wound care specialization to classify five key wound conditions, namely…
Interpretable estimation of the risk of heart failure hospitalization from a 30-second electrocardiogram
Sergio González, Wan-Ting Hsieh, Davide Burba +4
Survival modeling in healthcare relies on explainable statistical models; yet, their underlying assumptions are often simplistic and, thus, unrealistic. Machine learning models can…
A Mixed-Domain Self-Attention Network for Multilabel Cardiac Irregularity Classification Using Reduced-Lead Electrocardiogram
Hao-Chun Yang, Wan-Ting Hsieh, Trista Pei-Chun Chen
Electrocardiogram(ECG) is commonly used to detect cardiac irregularities such as atrial fibrillation, bradycardia, and other irregular complexes. While previous studies have achiev…
Domain-Generalized Textured Surface Anomaly Detection
Shang-Fu Chen, Yu-Min Liu, Chia-Ching Lin +2
Anomaly detection aims to identify abnormal data that deviates from the normal ones, while typically requiring a sufficient amount of normal data to train the model for performing…
Transition Motion Tensor: A Data-Driven Approach for Versatile and Controllable Agents in Physically Simulated Environments
Jonathan Hans Soeseno, Ying-Sheng Luo, Trista Pei-Chun Chen +1
This paper proposes the Transition Motion Tensor, a data-driven framework that creates novel and physically accurate transitions outside of the motion dataset. It enables simulated…
A Trainable Reconciliation Method for Hierarchical Time-Series
Davide Burba, Trista Chen
In numerous applications, it is required to produce forecasts for multiple time-series at different hierarchy levels. An obvious example is given by the supply chain in which deman…
TrustMAE: A Noise-Resilient Defect Classification Framework using Memory-Augmented Auto-Encoders with Trust Regions
Daniel Stanley Tan, Yi-Chun Chen, Trista Pei-Chun Chen +1
In this paper, we propose a framework called TrustMAE to address the problem of product defect classification. Instead of relying on defective images that are difficult to collect…
CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotion
Ying-Sheng Luo, Jonathan Hans Soeseno, Trista Pei-Chun Chen +1
Motion synthesis in a dynamic environment has been a long-standing problem for character animation. Methods using motion capture data tend to scale poorly in complex environments b…