no code implementations • 27 Apr 2024 • Toshitaka Hayashi, Dalibor Cimr, Hamido Fujita, Richard Cimler
This paper offers a comprehensive review of one-class classification (OCC), examining the technologies and methodologies employed in its implementation.
no code implementations • 27 Feb 2024 • Peng Gao, Shi-Min Li, Feng Gao, Fei Wang, Ru-Yue Yuan, Hamido Fujita
Deep learning-based methods monopolize the latest research in the field of thermal infrared (TIR) object tracking.
no code implementations • 2 Jul 2021 • Peng Gao, Feng Gao, Peng Wang, Jian-Cheng Ni, Fei Wang, Hamido Fujita
Multi-hop machine reading comprehension is a challenging task in natural language processing as it requires more reasoning ability across multiple documents.
no code implementations • 29 Feb 2020 • Yinglin Wang, Ming Wang, Hamido Fujita
Word Sense Disambiguation (WSD) has been a basic and on-going issue since its introduction in natural language processing (NLP) community.
Ranked #1 on Word Sense Disambiguation on Knowledge-based:
no code implementations • 16 Jan 2020 • Toshitaka Hayashi, Hamido Fujita
Zero-Shot Learning (ZSL) is the task of predicting class that is not in the training data(target class).
no code implementations • 27 Aug 2019 • Peng Gao, Qiquan Zhang, Fei Wang, Liyi Xiao, Hamido Fujita, Yan Zhang
Although numerous recent tracking approaches have made tremendous advances in the last decade, achieving high-performance visual tracking remains a challenge.
no code implementations • 23 Apr 2019 • Peng Gao, Ruyue Yuan, Fei Wang, Liyi Xiao, Hamido Fujita, Yan Zhang
In this paper, we investigate the impacts of three main aspects of visual tracking, i. e., the backbone network, the attentional mechanism, and the detection component, and propose a Siamese Attentional Keypoint Network, dubbed SATIN, for efficient tracking and accurate localization.
no code implementations • Information Sciences 2017 • U Rajendra Acharya. Hamido Fujita, Hamido Fujita, Shu Lih Oh, Yuki Hagiwara, Jen Hong Tan, Muhammad Adam
In this study, we implemented a convolutional neural network (CNN) algorithm for the automated detection of a normal and MI ECG beats (with noise and without noise).