1 code implementation • 21 Mar 2024 • Fei Li, Chu Kiong Loo, Wei Shiung Liew, Xiaofeng Liu
LI integrates a loop topology with layer-wise and end-to-end training, compatible with various neural network models.
1 code implementation • 7 Sep 2023 • Naoki Masuyama, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota
In the clustering domain, various algorithms with a federated learning framework (i. e., federated clustering) have been actively studied and showed high clustering performance while preserving data privacy.
no code implementations • 23 Jun 2023 • Chu Kiong Loo, Wei Shiung Liew, Stefan Wermter
ExLL outperforms all algorithms for accuracy in the majority of the tested scenarios.
1 code implementation • 1 May 2023 • Naoki Masuyama, Takanori Takebayashi, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi, Stefan Wermter
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 clustering performance.
1 code implementation • 12 Jun 2022 • Ghalib Ahmed Tahir, Chu Kiong Loo, Zongying Liu
During each training cycle of G-Specialist, a model is fine-tuned on the synthetic images generated by RQMixup, intermixing clean and distorted images of a particular distortion at a randomly chosen level.
1 code implementation • 11 Nov 2021 • Vadym Gryshchuk, Cornelius Weber, Chu Kiong Loo, Stefan Wermter
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 previously learned representations.
no code implementations • 21 Jun 2021 • Ghalib Tahir, Chu Kiong Loo
First, we will present the rationale of visual-based methods for food recognition.
1 code implementation • 2 Mar 2021 • Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi
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 approach for label probability computation.
no code implementations • 21 Apr 2020 • Fatai Sado, Chu Kiong Loo, Wei Shiung Liew, Matthias Kerzel, Stefan Wermter
The recent stance on the explainability of AI systems has witnessed several approaches on eXplainable Artificial Intelligence (XAI); however, most of the studies have focused on data-driven XAI systems applied in computational sciences.
no code implementations • 13 Sep 2015 • 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 brain of mammalian leads two distinct pathways in the model, which are specialized for analysis of motion (optic flow) and form information.
no code implementations • 2 Jun 2015 • Yuhuang Hu, M. S. Ishwarya, Chu Kiong Loo
This article demonstrates a new conceptor network based classifier in classifying images.