65 citations · 97 across the 28 of their papers we have counts for
18 papers · 1 filter
3D MRI-Based Alzheimer's Disease Classification Using Multi-Modal 3D CNN with Leakage-Aware Subject-Level Evaluation
Md Sifat, Sania Akter, Akif Islam +5
Deep learning has become an important tool for Alzheimer's disease (AD) classification from structural MRI. Many existing studies analyze individual 2D slices extracted from MRI vo…
Multi Class Parkinson Disease Detection Based on Finger Tapping Using Attention Enhanced CNN BiLSTM
Abu Saleh Musa Miah, Najmul Hassan, Md Maruf Al Hossain +2
Accurate evaluation of Parkinsons disease (PD) severity is essential for effective clinical management and intervention development. Despite the proposal of several gesture based P…
Oitijjo-3D: Generative AI Framework for Rapid 3D Heritage Reconstruction from Street View Imagery
Momen Khandoker Ope, Akif Islam, Mohd Ruhul Ameen +3
Cultural heritage restoration in Bangladesh faces a dual challenge of limited resources and scarce technical expertise. Traditional 3D digitization methods, such as photogrammetry…
Hybrid CNN-BYOL Approach for Fault Detection in Induction Motors Using Thermal Images
Tangin Amir Smrity, MD Zahin Muntaqim Hasan Muhammad Kafi, Abu Saleh Musa Miah +5
Induction motors (IMs) are indispensable in industrial and daily life, but they are susceptible to various faults that can lead to overheating, wasted energy consumption, and servi…
Electromyography-Based Gesture Recognition: Hierarchical Feature Extraction for Enhanced Spatial-Temporal Dynamics
Jungpil Shin, Abu Saleh Musa Miah, Sota Konnai +2
Hand gesture recognition using multichannel surface electromyography (sEMG) is challenging due to unstable predictions and inefficient time-varying feature enhancement. To overcome…
Stack Transformer Based Spatial-Temporal Attention Model for Dynamic Sign Language and Fingerspelling Recognition
Koki Hirooka, Abu Saleh Musa Miah, Tatsuya Murakami +3
Hand gesture-based Sign Language Recognition (SLR) serves as a crucial communication bridge between deaf and non-deaf individuals. While Graph Convolutional Networks (GCNs) are com…
IoT-Based Real-Time Medical-Related Human Activity Recognition Using Skeletons and Multi-Stage Deep Learning for Healthcare
Subrata Kumer Paul, Abu Saleh Musa Miah, Rakhi Rani Paul +3
The Internet of Things (IoT) and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients. Recognizing medical-related…
ChatGPT in Research and Education: Exploring Benefits and Threats
Abu Saleh Musa Miah, Md Mahbubur Rahman Tusher, Md. Moazzem Hossain +5
In recent years, advanced artificial intelligence technologies, such as ChatGPT, have significantly impacted various fields, including education and research. Developed by OpenAI,…
FireLite: Leveraging Transfer Learning for Efficient Fire Detection in Resource-Constrained Environments
Mahamudul Hasan, Md Maruf Al Hossain Prince, Mohammad Samar Ansari +3
Fire hazards are extremely dangerous, particularly in sectors such as the transportation industry, where political unrest increases the likelihood of their occurrence. By employing…
Multimodal Attention-Enhanced Feature Fusion-based Weekly Supervised Anomaly Violence Detection
Yuta Kaneko, Abu Saleh Musa Miah, Najmul Hassan +3
Weakly supervised video anomaly detection (WS-VAD) is a crucial area in computer vision for developing intelligent surveillance systems. This system uses three feature streams: RGB…
A Comprehensive Methodological Survey of Human Activity Recognition Across Divers Data Modalities
Jungpil Shin, Najmul Hassan, Abu Saleh Musa Miah1 +1
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…
Bengali Sign Language Recognition through Hand Pose Estimation using Multi-Branch Spatial-Temporal Attention Model
Abu Saleh Musa Miah, Md. Al Mehedi Hasan, Md Hadiuzzaman +2
Hand gesture-based sign language recognition (SLR) is one of the most advanced applications of machine learning, and computer vision uses hand gestures. Although, in the past few y…
EMG-Based Hand Gesture Recognition through Diverse Domain Feature Enhancement and Machine Learning-Based Approach
Abu Saleh Musa Miah, Najmul Hassan, Md. Maniruzzaman +2
Surface electromyography (EMG) serves as a pivotal tool in hand gesture recognition and human-computer interaction, offering a non-invasive means of signal acquisition. This study…
Computer-Aided Fall Recognition Using a Three-Stream Spatial-Temporal GCN Model with Adaptive Feature Aggregation
Jungpil Shin, Abu Saleh Musa Miah, Rei Egawa1 +4
The prevention of falls is paramount in modern healthcare, particularly for the elderly, as falls can lead to severe injuries or even fatalities. Additionally, the growing incidenc…
Multichannel Attention Networks with Ensembled Transfer Learning to Recognize Bangla Handwritten Charecter
Farhanul Haque, Md. Al-Hasan, Sumaiya Tabssum Mou +3
The Bengali language is the 5th most spoken native and 7th most spoken language in the world, and Bengali handwritten character recognition has attracted researchers for decades. H…
BAUST Lipi: A BdSL Dataset with Deep Learning Based Bangla Sign Language Recognition
Md Hadiuzzaman, Mohammed Sowket Ali, Tamanna Sultana +3
People commonly communicate in English, Arabic, and Bengali spoken languages through various mediums. However, deaf and hard-of-hearing individuals primarily use body language and…
An Advanced Deep Learning Based Three-Stream Hybrid Model for Dynamic Hand Gesture Recognition
Md Abdur Rahim, Abu Saleh Musa Miah, Hemel Sharker Akash +3
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, h…
A Methodological and Structural Review of Hand Gesture Recognition Across Diverse Data Modalities
Jungpil Shin, Abu Saleh Musa Miah, Md. Humaun Kabir +2
Researchers have been developing Hand Gesture Recognition (HGR) systems to enhance natural, efficient, and authentic human-computer interaction, especially benefiting those who rel…