551 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Swakkhar Shatabda2 profiles20 · h 31
- Sami Azam2 profiles8 · h 14
- C. R. Rahman7 · h 6
- Mohaimenul Azam Khan Raiaan2 profiles7 · h 13
- Md. Rafiqul Islam6 · h 1
- Chowdhury Mofizur Rahman3 profiles4 · h 17
- Sajid Ahmed4 · h 13
- S. Islam4 · h 17
- A. Khandoker3 · h 38
- Arefin Ittesafun Abian3 · h 3
- D. Farid3 · h 25
- Fahim Hafiz3 · h 3
- BRAC UniversityBD9 papers
- Bangladesh University of Engineering and TechnologyBD8 papers
- Charles Darwin UniversityAU8 papers
- Pennsylvania State UniversityUS6 papers
- Artificial Intelligence in Medicine (Canada)CA5 papers
- Monash UniversityAU5 papers
- North South UniversityBD4 papers
- University of DhakaBD4 papers
- Khalifa University of Science and TechnologyAE3 papers
- Lappeenranta-Lahti University of TechnologyFI3 papers
- Stamford University BangladeshBD3 papers
- University of Asia PacificBD3 papers
62 papers
TextEconomizer: Enhancing Lossy Text Compression with Denoising Transformers and Entropy Coding
Mahbub E Sobhani, Anika Tasnim Rodela, Chowdhury Mofizur Rahman +2
Lossy text compression reduces data size while preserving core meaning, making it well-suited for summarization, automated analysis, and digital archives. Despite the dominance of…
Automated detection of pediatric congenital heart disease from phonocardiograms using deep and handcrafted feature fusion
Abdul Jabbar, Ethan Grooby, Yang Yi Poh +5
Congenital heart disease (CHD) is the most common type of birth defect, impacting about 1% of live births worldwide. Echocardiography, the gold-standard diagnostic method, is costl…
Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework
Md Muntasir Jahid Ayan, Md. Shahriar Rashid, Tazzina Afroze Hassan +6
The increasing complexity and frequency of cyber-threats demand intrusion detection systems (IDS) that are not only accurate but also interpretable. This paper presented a novel ID…
Vision Models for Medical Imaging: A Hybrid Approach for PCOS Detection from Ultrasound Scans
Md Mahmudul Hoque, Md Mehedi Hassain, Muntakimur Rahaman +3
Polycystic Ovary Syndrome (PCOS) is the most familiar endocrine illness in women of reproductive age. Many Bangladeshi women suffer from PCOS disease in their older age. The aim of…
Mitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation
Musarrat Zeba, Abdullah Al Mamun, Kishoar Jahan Tithee +8
In healthcare, it is essential for any Large Language Model (LLM)-generated output to be reliable and accurate, particularly in cases involving decision-making and patient safety.…
TinyLLM: Evaluation and Optimization of Small Language Models for Agentic Tasks on Edge Devices
Mohd Ariful Haque, Fahad Rahman, Kishor Datta Gupta +2
This paper investigates the effectiveness of small language models (SLMs) for agentic tasks (function/tool/API calling) with a focus on running agents on edge devices without relia…
Hybrid Si-GST Polarization-Insensitive Dynamically Tunable Bifocal Metalens Operating at 1.55-m Wavelength
Dipika Rani Nath, Sadid Muneer, Sajid Muhaimin Choudhury
Metasurfaces have become a cornerstone of flat-optics, enabling precise control over light propagation through nanoengineered materials. Dynamic and reconfigurable metalenses are k…
Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances
Wasimul Karim, Riasad Alvi, Sayeem Been Zaman +7
Generative artificial intelligence (GenAI) is transforming bioinformatics by advancing genomics, proteomics, transcriptomics, structural biology, and drug discovery. Following the…
BioAutoML-NAS: An End-to-End AutoML Framework for Multimodal Insect Classification via Neural Architecture Search on Large-Scale Biodiversity Data
Arefin Ittesafun Abian, Debopom Sutradhar, Md Rafi Ur Rashid +5
Insect classification is important for agricultural management and ecological research, as it directly affects crop health and production. However, this task remains challenging du…
Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models
Subhey Sadi Rahman, Md. Adnanul Islam, Md. Mahbub Alam +5
Large Language Models (LLMs) are trained on vast and diverse internet corpora that often include inaccurate or misleading content. Consequently, LLMs can generate misinformation, m…
A fine-grained attention and geometric correspondence model for musculoskeletal risk classification in athletes using multimodal visual and skeletal features
Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Tamanna Shermin +3
Musculoskeletal disorders pose significant risks to athletes, and early risk assessment is essential for prevention. However, most existing methods are designed for controlled sett…
From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users
Sadia Sultana Chowa, Riasad Alvi, Subhey Sadi Rahman +5
The pursuit of human-level artificial intelligence (AI) has significantly advanced the development of autonomous agents and Large Language Models (LLMs). LLMs are now widely utiliz…
HANS-Net: Hyperbolic Convolution and Adaptive Temporal Attention for Accurate and Generalizable Liver and Tumor Segmentation in CT Imaging
Arefin Ittesafun Abian, Ripon Kumar Debnath, Md. Abdur Rahman +5
Accurate liver and tumor segmentation on abdominal CT images is critical for reliable diagnosis and treatment planning, but remains challenging due to complex anatomical structures…
TritonZ: A Remotely Operated Underwater Rover with Manipulator Arm for Exploration and Rescue Operations
Kawser Ahmed, Mir Shahriar Fardin, Md Arif Faysal Nayem +2
The increasing demand for underwater exploration and rescue operations enforces the development of advanced wireless or semi-wireless underwater vessels equipped with manipulator a…
A deep learning and machine learning approach to predict neonatal death in the context of São Paulo
Mohon Raihan, Plabon Kumar Saha, Rajan Das Gupta +6
Neonatal death is still a concerning reality for underdeveloped and even some developed countries. Worldwide data indicate that 26.693 babies out of 1,000 births die, according to…
GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association prediction
Ummay Maria Muna, Fahim Hafiz, Shanta Biswas +1
Small nucleolar RNAs (snoRNAs) are increasingly recognized for their critical role in the pathogenesis and characterization of various human diseases. Consequently, the precise ide…
HingeRLC-GAN: Combating Mode Collapse with Hinge Loss and RLC Regularization
Osman Goni, Himadri Saha Arka, Mithun Halder +2
Recent advances in Generative Adversarial Networks (GANs) have demonstrated their capability for producing high-quality images. However, a significant challenge remains mode collap…
Three-dimensional imaging of biological cells using surface plasmon coupled emission
Anik Mazumder, Mohammad Mozammal, Muhammad Anisuzzaman Talukder
Biological cell imaging has become one of the most crucial research interests due to its wide-ranging applications in biomedical and microbiology studies. However, three-dimensiona…
Design of a Microprocessors and Microcontrollers Laboratory Course Addressing Complex Engineering Problems and Activities
Fahim Hafiz, Md Jahidul Hoq Emon, Md Abid Hossain +3
This paper proposes a novel curriculum for the microprocessors and microcontrollers laboratory course. The proposed curriculum blends structured laboratory experiments with an open…
Adaptive Tabu Dropout for Regularization of Deep Neural Network
Md. Tarek Hasan, Arifa Akter, Mohammad Nazmush Shamael +4
Dropout is an effective strategy for the regularization of deep neural networks. Applying tabu to the units that have been dropped in the recent epoch and retaining them for traini…
An Enhanced Text Compression Approach Using Transformer-based Language Models
Chowdhury Mofizur Rahman, Mahbub E Sobhani, Anika Tasnim Rodela +1
Text compression shrinks textual data while keeping crucial information, eradicating constraints on storage, bandwidth, and computational efficacy. The integration of lossless comp…
Accurate Water Level Monitoring in AWD Rice Cultivation Using Convolutional Neural Networks
Ahmed Rafi Hasan, Niloy Kumar Kundu, Saad Hasan +2
The Alternate Wetting and Drying (AWD) method is a rice-growing water management technique promoted as a sustainable alternative to Continuous Flooding (CF). Climate change has pla…
A Bidirectional Siamese Recurrent Neural Network for Accurate Gait Recognition Using Body Landmarks
Proma Hossain Progga, Md. Jobayer Rahman, Swapnil Biswas +3
Gait recognition is a significant biometric technique for person identification, particularly in scenarios where other physiological biometrics are impractical or ineffective. In t…
DUA-D2C: Dynamic Uncertainty Aware Method for Overfitting Remediation in Deep Learning
Md. Saiful Bari Siddiqui, Md Mohaiminul Islam, Md. Golam Rabiul Alam
Overfitting remains a significant challenge in deep learning, often arising from data outliers, noise, and limited training data. To address this, we previously proposed the Divide…