90 citations · 264 across the 28 of their papers we have counts for
28 papers
DyCAF-Net: Dynamic Class-Aware Fusion Network
Md Abrar Jahin, Shahriar Soudeep, M. F. Mridha +2
Recent advancements in object detection rely on modular architectures with multi-scale fusion and attention mechanisms. However, static fusion heuristics and class-agnostic attenti…
Reinforcement-Guided Hyper-Heuristic Hyperparameter Optimization for Fair and Explainable Spiking Neural Network-Based Financial Fraud Detection
Sadman Mohammad Nasif, Md Abrar Jahin, M. F. Mridha
The growing adoption of home banking systems has increased cyberfraud risks, requiring detection models that are accurate, fair, and explainable. While AI methods show promise, the…
AdeptHEQ-FL: Adaptive Homomorphic Encryption for Federated Learning of Hybrid Classical-Quantum Models with Dynamic Layer Sparing
Md Abrar Jahin, Taufikur Rahman Fuad, M. F. Mridha +2
Federated Learning (FL) faces inherent challenges in balancing model performance, privacy preservation, and communication efficiency, especially in non-IID decentralized environmen…
Quantum-Informed Contrastive Learning with Dynamic Mixup Augmentation for Class-Imbalanced Expert Systems
Md Abrar Jahin, Adiba Abid, M. F. Mridha
Expert systems often operate in domains characterized by class-imbalanced tabular data, where detecting rare but critical instances is essential for safety and reliability. While c…
Vision Transformers for End-to-End Quark-Gluon Jet Classification from Calorimeter Images
Md Abrar Jahin, Shahriar Soudeep, Arian Rahman Aditta +3
Distinguishing between quark- and gluon-initiated jets is a critical and challenging task in high-energy physics, pivotal for improving new physics searches and precision measureme…
Soybean Disease Detection via Interpretable Hybrid CNN-GNN: Integrating MobileNetV2 and GraphSAGE with Cross-Modal Attention
Md Abrar Jahin, Soudeep Shahriar, M. F. Mridha +2
Soybean leaf disease detection is critical for agricultural productivity but faces challenges due to visually similar symptoms and limited interpretability in conventional methods.…
Co-AttenDWG: Co-Attentive Dimension-Wise Gating and Expert Fusion for Multi-Modal Offensive Content Detection
Md. Mithun Hossain, Md. Shakil Hossain, Sudipto Chaki +1
Multi-modal learning has emerged as a crucial research direction, as integrating textual and visual information can substantially enhance performance in tasks such as classificatio…
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion Detection
Md Abrar Jahin, Shahriar Soudeep, Fahmid Al Farid +4
Cybersecurity threats are growing, making network intrusion detection essential. Traditional machine learning models remain effective in resource-limited environments due to their…
MobilePlantViT: A Mobile-friendly Hybrid ViT for Generalized Plant Disease Image Classification
Moshiur Rahman Tonmoy, Md. Mithun Hossain, Nilanjan Dey +1
Plant diseases significantly threaten global food security by reducing crop yields and undermining agricultural sustainability. AI-driven automated classification has emerged as a…
A Unified Framework for Evaluating and Enhancing the Transparency of Explainable AI Methods via Perturbation-Gradient Consensus Attribution
Md. Ariful Islam, Md Abrar Jahin, M. F. Mridha +1
Explainable Artificial Intelligence (XAI) methods are increasingly used in safety-critical domains, yet there is no unified framework to jointly evaluate fidelity, interpretability…
Interpretable Dynamic Graph Neural Networks for Small Occluded Object Detection and Tracking
Shahriar Soudeep, Md Abrar Jahin, M. F. Mridha
The detection and tracking of small, occluded objects such as pedestrians, cyclists, and motorbikes pose significant challenges for traffic surveillance systems because of their er…
Designing Cellular Manufacturing Systems in the Presence of Alternative Process Plans
Md. Kutub Uddin, Md. Saiful Islam, Md Abrar Jahin +3
In the design of cellular manufacturing systems (CMS), numerous technological and managerial decisions must be made at both the design and operational stages. The first step in des…
Solving Generalized Grouping Problems in Cellular Manufacturing Systems Using a Network Flow Model
Md. Kutub Uddin, Md. Saiful Islam, Md Abrar Jahin +2
This paper focuses on the generalized grouping problem in the context of cellular manufacturing systems (CMS), where parts may have more than one process route. A process route lis…
Human-in-the-Loop Feature Selection Using Interpretable Kolmogorov-Arnold Network-based Double Deep Q-Network
Md Abrar Jahin, M. F. Mridha, Nilanjan Dey +1
Feature selection is critical for improving the performance and interpretability of machine learning models, particularly in high-dimensional spaces where complex feature interacti…
Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination
Md Abrar Jahin, Md. Akmol Masud, M. F. Mridha +2
In high-energy physics, particle jet tagging plays a pivotal role in distinguishing quark from gluon jets using data from collider experiments. While graph-based deep learning meth…
Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics
Md Abrar Jahin, Md. Akmol Masud, Md Wahiduzzaman Suva +2
The rapid data surge from the high-luminosity Large Hadron Collider introduces critical computational challenges requiring novel approaches for efficient data processing in particl…
KACQ-DCNN: Uncertainty-Aware Interpretable Kolmogorov-Arnold Classical-Quantum Dual-Channel Neural Network for Heart Disease Detection
Md Abrar Jahin, Md. Akmol Masud, M. F. Mridha +2
Heart failure is a leading cause of global mortality, necessitating improved diagnostic strategies. Classical machine learning models struggle with challenges such as high-dimensio…
TriQXNet: Forecasting Dst Index from Solar Wind Data Using an Interpretable Parallel Classical-Quantum Framework with Uncertainty Quantification
Md Abrar Jahin, M. F. Mridha, Zeyar Aung +2
Geomagnetic storms, caused by solar wind energy transfer to Earth's magnetic field, can disrupt critical infrastructure like GPS, satellite communications, and power grids. The dis…
Optimizing Container Loading and Unloading through Dual-Cycling and Dockyard Rehandle Reduction Using a Hybrid Genetic Algorithm
Md. Mahfuzur Rahman, Md Abrar Jahin, Md. Saiful Islam +1
This paper addresses the NP-hard problem of optimizing container handling at ports by integrating Quay Crane Dual-Cycling (QCDC) and dockyard rehandle minimization. We realized tha…
A hybrid transformer and attention based recurrent neural network for robust and interpretable sentiment analysis of tweets
Md Abrar Jahin, Md Sakib Hossain Shovon, M. F. Mridha +2
Sentiment analysis is crucial for understanding public opinion and consumer behavior. Existing models face challenges with linguistic diversity, generalizability, and explainabilit…
Predicting Male Domestic Violence Using Explainable Ensemble Learning and Exploratory Data Analysis
Md Abrar Jahin, Saleh Akram Naife, Fatema Tuj Johora Lima +2
Domestic violence is commonly viewed as a gendered issue that primarily affects women, which tends to leave male victims largely overlooked. This study presents a novel, data-drive…
Ergonomic Design of Computer Laboratory Furniture: Mismatch Analysis Utilizing Anthropometric Data of University Students
Anik Kumar Saha, Md Abrar Jahin, Md. Rafiquzzaman +1
Many studies have shown how ergonomically designed furniture improves productivity and well-being. As computers have become a part of students' academic lives, they will grow furth…
Analysis of Internet of Things Implementation Barriers in the Cold Supply Chain: An Integrated ISM-MICMAC and DEMATEL Approach
Kazrin Ahmad, Md. Saiful Islam, Md Abrar Jahin +1
Integrating Internet of Things (IoT) technology inside the cold supply chain can enhance transparency, efficiency, and quality, optimizing operating procedures and increasing produ…
AI in Supply Chain Risk Assessment: A Systematic Literature Review and Bibliometric Analysis
Md Abrar Jahin, Saleh Akram Naife, Anik Kumar Saha +1
Supply chain risk assessment (SCRA) is pivotal for ensuring resilience in increasingly complex global supply networks. While existing reviews have explored traditional methodologie…