65 citations · 97 across the 28 of their papers we have counts for
32 papers
PermitGPT: A Unified Generative-AI Pipeline for Construction Hazard Forecasting, Permit Prediction, and Community Impact
Mohd Ruhul Ameen, Farjana Aktar, Akif Islam +3
Urban construction governance requires early decisions that connect workplace safety, permitting requirements, and community impact, yet the relevant evidence is often scattered ac…
Prompt Control-Flow Integrity: A Priority-Aware Runtime Defense Against Prompt Injection in LLM Systems
Md Takrim Ul Alam, Akif Islam, Mohd Ruhul Ameen +2
Large language models (LLMs) deployed behind APIs and retrieval-augmented generation (RAG) stacks are vulnerable to prompt injection attacks that may override system policies, subv…
Critical Thinking in the Age of Artificial Intelligence: A Survey-Based Study with Machine Learning Insights
M Murshidul Bari, Akif Islam, Mohd Ruhul Ameen +2
The growing use of artificial intelligence (AI) in education, professional work, and everyday problem-solving has raised important questions about its effect on human reasoning. Wh…
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…
Teaching Machine Learning Through Cricket: A Practical Engineering Education Approach
Mohd Ruhul Ameen, Akif Islam, Abu Saleh Musa Miah +2
Teaching complex machine learning concepts such as reinforcement learning and Markov Decision Processes remains challenging in engineering education. Students often struggle to con…
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…
Code Smell Detection via Pearson Correlation and ML Hyperparameter Optimization
Moinuddin Muhammad Imtiaz Bhuiyan, Kazi Ekramul Hoque, Rakibul Islam +6
This study addresses the challenge of detecting code smells in large-scale software systems using machine learning (ML). Traditional detection methods often suffer from low accurac…
Quantifying Affective Bias in Low-Resource Media: Large-Scale Emotion Profiling of Bengali Headlines
Mohd Ruhul Ameen, Akif Islam, Ayesha Siddiqua +2
News media can influence readers not only through the events they report but also through the emotional tone used to present them. This issue is especially important in digital new…
A Methodological and Structural Review of Parkinsons Disease Detection Across Diverse Data Modalities
Abu Saleh Musa Miah, taro Suzuki, Jungpil Shin
Parkinsons Disease (PD) is a progressive neurological disorder that primarily affects motor functions and can lead to mild cognitive impairment (MCI) and dementia in its advanced s…
Classification of ADHD and Healthy Children Using EEG Based Multi-Band Spatial Features Enhancement
Md Bayazid Hossain, Md Anwarul Islam Himel, Md Abdur Rahim +3
Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children, characterized by difficulties in attention, hyperactivity, and impulsivity. Ear…
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…
Machine Learning-Based Differential Diagnosis of Parkinson's Disease Using Kinematic Feature Extraction and Selection
Masahiro Matsumoto, Abu Saleh Musa Miah, Nobuyoshi Asai +1
Parkinson's disease (PD), the second most common neurodegenerative disorder, is characterized by dopaminergic neuron loss and the accumulation of abnormal synuclein. PD presents bo…
Parkinson Disease Detection Based on In-air Dynamics Feature Extraction and Selection Using Machine Learning
Jungpil Shin, Abu Saleh Musa Miah, Koki Hirooka +2
Parkinson's disease (PD) is a progressive neurological disorder that impairs movement control, leading to symptoms such as tremors, stiffness, and bradykinesia. Many researchers an…
Computer-Aided Osteoporosis Diagnosis Using Transfer Learning with Enhanced Features from Stacked Deep Learning Modules
Ayesha Siddiqua, Rakibul Hasan, Anichur Rahman +1
Knee osteoporosis weakens the bone tissue in the knee joint, increasing fracture risk. Early detection through X-ray images enables timely intervention and improved patient outcome…
Multi-class heart disease Detection, Classification, and Prediction using Machine Learning Models
Mahfuzul Haque, Abu Saleh Musa Miah, Debashish Gupta +5
Heart disease is a leading cause of premature death worldwide, particularly among middle-aged and older adults, with men experiencing a higher prevalence. According to the World He…
Enhancing PTSD Outcome Prediction with Ensemble Models in Disaster Contexts
Ayesha Siddiqua, Atib Mohammad Oni, Abu Saleh Musa Miah +1
Post-traumatic stress disorder (PTSD) is a significant mental health challenge that affects individuals exposed to traumatic events. Early detection and effective intervention for…
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…