Korean sign language alphabet recognition through the integration of handcrafted and deep learning-based two-stream feature extraction approach

J Shin, ASM Miah, Y Akiba, K Hirooka, N Hassan… - IEEE …, 2024 - ieeexplore.ieee.org
Recognizing sign language plays a crucial role in improving communication accessibility for
the Deaf and hard-of-hearing communities. In Korea, many individuals facing hearing and …

Anomaly detection in weakly supervised videos using multistage graphs and general deep learning based spatial-temporal feature enhancement

J Shin, Y Kaneko, ASM Miah, N Hassan… - IEEE …, 2024 - ieeexplore.ieee.org
Weakly supervised video anomaly detection (WS-VAD) is a crucial research domain in
computer vision for the implementation of intelligent surveillance systems. Many researchers …

An advanced deep learning based three-stream hybrid model for dynamic hand gesture recognition

MA Rahim, ASM Miah, HS Akash, J Shin… - arxiv preprint arxiv …, 2024 - arxiv.org
In the modern context, hand gesture recognition has emerged as a focal point. This is due to
its wide range of applications, which include comprehending sign language, factories …

Artificial intelligence in sign language recognition: A comprehensive bibliometric and visual analysis

Y Zhang, Y Han, Z Zhu, X Jiang, Y Zhang - Computers and Electrical …, 2024 - Elsevier
Sign language recognition (SLR) plays a crucial role in bridging the communication gap
between individuals with hearing impairments and the auditory communities. This study …

Hand gesture recognition using sEMG signals with a multi-stream time-varying feature enhancement approach

J Shin, ASM Miah, S Konnai, I Takahashi, K Hirooka - Scientific Reports, 2024 - nature.com
Hand gesture recognition based on sparse multichannel surface electromyography (sEMG)
still poses a significant challenge to deployment as a muscle–computer interface. Many …

FireLite: Leveraging Transfer Learning for Efficient Fire Detection in Resource-Constrained Environments

M Hasan, MMAH Prince, MS Ansari, S Jahan… - arxiv preprint arxiv …, 2024 - arxiv.org
Fire hazards are extremely dangerous, particularly in sectors such as the transportation
industry, where political unrest increases the likelihood of their occurrence. By employing IP …

A Comprehensive Methodological Survey of Human Activity Recognition Across Divers Data Modalities

J Shin, N Hassan, ASM Miah, S Nishimura - arxiv preprint arxiv …, 2024 - arxiv.org
Human Activity Recognition (HAR) systems aim to understand human behaviour and assign
a label to each action, attracting significant attention in computer vision due to their wide …

[HTML][HTML] Two-Stream Modality-Based Deep Learning Approach for Enhanced Two-Person Human Interaction Recognition in Videos

HS Akash, MA Rahim, ASM Miah, HS Lee, SW Jang… - Sensors, 2024 - mdpi.com
Human interaction recognition (HIR) between two people in videos is a critical field in
computer vision and pattern recognition, aimed at identifying and understanding human …

Holistic-Based Cross-Attention Modal Fusion Network for Video Sign Language Recognition

Q Gao, J Hu, H Mai, Z Ju - IEEE Transactions on Computational …, 2024 - ieeexplore.ieee.org
As a bridge between the deaf people and the outside, sign language primarily involves hand
movements, complemented by intricate facial and body expressions. To enhance the …

Multimodal Attention-Enhanced Feature Fusion-Based Weakly Supervised Anomaly Violence Detection

J Shin, ASM Miah, Y Kaneko, N Hassan… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Weakly supervised video anomaly detection (WS-VAD) plays a pivotal role in advancing
intelligent surveillance systems within the field of computer vision. Despite significant …