26 citations · 56 across the 15 of their papers we have counts for
16 papers
MoTop: Motion-Topological Model For Micro AU Detection
Huai-Qian Khor, Mengting Wei, Yante Li +2
Facial micro-expressions are spontaneous, brief, and subtle facial movements that reveal suppressed emotions in high-stakes environments. In contrast to classic expression analysis…
PHIDA: Persistence-Guided Node-to-Cluster Mapping for Online Clustering
Naoki Masuyama, Yusuke Nojima, Stefan Wermter +3
Online clustering methods that adaptively create and update nodes as data arrive often make node learning explicit, whereas the mapping from the learned node state to output cluste…
Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory
Naoki Masuyama, Yusuke Nojima, Yuichiro Toda +3
With the increasing importance of data privacy protection, various privacy-preserving machine learning methods have been proposed. In the clustering domain, various algorithms with…
Explainable Lifelong Stream Learning Based on "Glocal" Pairwise Fusion
Chu Kiong Loo, Wei Shiung Liew, Stefan Wermter
Real-time on-device continual learning applications are used on mobile phones, consumer robots, and smart appliances. Such devices have limited processing and memory storage capabi…
A Parameter-free Adaptive Resonance Theory-based Topological Clustering Algorithm Capable of Continual Learning
Naoki Masuyama, Takanori Takebayashi, Yusuke Nojima +3
In general, a similarity threshold (i.e., a vigilance parameter) for a node learning process in Adaptive Resonance Theory (ART)-based algorithms has a significant impact on cluster…
Modeling Generalized Specialist Approach To Train Quality Resilient Snapshot Ensemble
Ghalib Ahmed Tahir, Chu Kiong Loo, Zongying Liu
Convolutional neural networks (CNNs) apply well with food image recognition due to the ability to learn discriminative visual features. Nevertheless, recognizing distorted images i…
Novel Multicolumn Kernel Extreme Learning Machine for Food Detection via Optimal Features from CNN
Ghalib Ahmed Tahir, Chu Kiong Loo
Automatic food detection is an emerging topic of interest due to its wide array of applications ranging from detecting food images on social media platforms to filtering non-food p…
Lifelong Learning from Event-based Data
Vadym Gryshchuk, Cornelius Weber, Chu Kiong Loo +1
Lifelong learning is a long-standing aim for artificial agents that act in dynamic environments, in which an agent needs to accumulate knowledge incrementally without forgetting pr…
A Comprehensive Survey of Image-Based Food Recognition and Volume Estimation Methods for Dietary Assessment
Ghalib Tahir, Chu Kiong Loo
Dietary studies showed that dietary-related problem such as obesity is associated with other chronic diseases like hypertension, irregular blood sugar levels, and increased risk of…
Multi-label Classification via Adaptive Resonance Theory-based Clustering
Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo +1
This paper proposes a multi-label classification algorithm capable of continual learning by applying an Adaptive Resonance Theory (ART)-based clustering algorithm and the Bayesian…
A Review of Critical Features and General Issues of Freely Available mHealth Apps For Dietary Assessment
Ghalib Ahmed Tahir, Chu Kiong Loo, Foong Ming Moy +1
Obesity is known to lower the quality of life substantially. It is often associated with increased chances of non-communicable diseases such as diabetes, cardiovascular problems, v…
Explainable Goal-Driven Agents and Robots -- A Comprehensive Review
Fatai Sado, Chu Kiong Loo, Wei Shiung Liew +2
Recent applications of autonomous agents and robots, such as self-driving cars, scenario-based trainers, exploration robots, and service robots have brought attention to crucial tr…
A Dual Fast and Slow Feature Interaction in Biologically Inspired Visual Recognition of Human Action
Bardia Yousefi, C. K. Loo
Computational neuroscience studies that have examined human visual system through functional magnetic resonance imaging (fMRI) have identified a model where the mammalian brain pur…
Bio-Inspired Human Action Recognition using Hybrid Max-Product Neuro-Fuzzy Classifier and Quantum-Behaved PSO
Bardia Yousefi, Chu Kiong Loo
Studies on computational neuroscience through functional magnetic resonance imaging (fMRI) and following biological inspired system stated that human action recognition in the brai…
Classify Images with Conceptor Network
Yuhuang Hu, M. S. Ishwarya, Chu Kiong Loo
This article demonstrates a new conceptor network based classifier in classifying images. Mathematical descriptions and analysis are presented. Various tests are experimented using…
Perceiving Motion Cues Inspired by Microsoft Kinect Sensor on Game Experiencing
Jiawei Xu, Shigang Yue, Ruisheng Wang +1
This paper proposed a novel method to replace the traditional mouse controller by using Microsoft Kinect Sensor to realize the functional implementation on human-machine interactio…