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Found 10 papers, 1 papers with code
A Closer Look at Geometric Temporal Dynamics for Face Anti-Spoofing
Face anti-spoofing (FAS) is indispensable for a face recognition system.
Streamlined Framework for Agile Forecasting Model Development towards Efficient Inventory Management
This paper proposes a framework for developing forecasting models by streamlining the connections between core components of the developmental process.
Kinship Representation Learning with Face Componential Relation
Kinship recognition aims to determine whether the subjects in two facial images are kin or non-kin, which is an emerging and challenging problem.
Development of a deep learning-based tool to assist wound classification
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 deep wound, infected wound, arterial wound, venous wound, and pressure wound, given color images captured using readily available cameras.
Interpretable estimation of the risk of heart failure hospitalization from a 30-second electrocardiogram
Survival modeling in healthcare relies on explainable statistical models; yet, their underlying assumptions are often simplistic and, thus, unrealistic.
A Mixed-Domain Self-Attention Network for Multilabel Cardiac Irregularity Classification Using Reduced-Lead Electrocardiogram
Electrocardiogram(ECG) is commonly used to detect cardiac irregularities such as atrial fibrillation, bradycardia, and other irregular complexes.
Domain-Generalized Textured Surface Anomaly Detection
By observing normal and abnormal surface data across multiple source domains, our model is expected to be generalized to an unseen textured surface of interest, in which only a small number of normal data can be observed during testing.
Transition Motion Tensor: A Data-Driven Approach for Versatile and Controllable Agents in Physically Simulated Environments
This paper proposes the Transition Motion Tensor, a data-driven framework that creates novel and physically accurate transitions outside of the motion dataset.
TrustMAE: A Noise-Resilient Defect Classification Framework using Memory-Augmented Auto-Encoders with Trust Regions
In this paper, we propose a framework called TrustMAE to address the problem of product defect classification.
CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotion
Motion synthesis in a dynamic environment has been a long-standing problem for character animation.
