17 citations · 22 across the 17 of their papers we have counts for
17 papers
Multi-Head Attention based interaction-aware architecture for Bangla Handwritten Character Recognition: Introducing a Primary Dataset
Mirza Raquib, Asif Pervez Polok, Kedar Nath Biswas +3
Character recognition is the fundamental part of an optical character recognition (OCR) system. Word recognition, sentence transcription, document digitization, and language proces…
A Depth-Aware Comparative Study of Euclidean and Hyperbolic Graph Neural Networks on Bitcoin Transaction Systems
Ankit Ghimire, Saydul Akbar Murad, Nick Rahimi
Bitcoin transaction networks are large scale socio- technical systems in which activities are represented through multi-hop interaction patterns. Graph Neural Networks(GNNs) have b…
A Fusion of context-aware based BanglaBERT and Two-Layer Stacked LSTM Framework for Multi-Label Cyberbullying Detection
Mirza Raquib, Asif Pervez Polok, Kedar Nath Biswas +3
Cyberbullying has become a serious and growing concern in todays virtual world. When left unnoticed, it can have adverse consequences for social and mental health. Researchers have…
Robust and Real-Time Bangladeshi Currency Recognition: A Dual-Stream MobileNet and EfficientNet Approach
Subreena, Mohammad Amzad Hossain, Mirza Raquib +4
Accurate currency recognition is essential for assistive technologies, particularly for visually impaired individuals who rely on others to identify banknotes. This dependency puts…
Gamma2Patterns: Deep Cognitive Attention Region Identification and Gamma-Alpha Pattern Analysis
Sobhana Jahan, Saydul Akbar Murad, Nick Rahimi +1
Deep cognitive attention is characterized by heightened gamma oscillations and coordinated visual behavior. Despite the physiological importance of these mechanisms, computational…
A Unified BERT-CNN-BiLSTM Framework for Simultaneous Headline Classification and Sentiment Analysis of Bangla News
Mirza Raquib, Munazer Montasir Akash, Tawhid Ahmed +5
In our daily lives, newspapers are an essential information source that impacts how the public talks about present-day issues. However, effectively navigating the vast amount of ne…
PSO-XAI: A PSO-Enhanced Explainable AI Framework for Reliable Breast Cancer Detection
Mirza Raquib, Niloy Das, Farida Siddiqi Prity +5
Breast cancer is considered the most critical and frequently diagnosed cancer in women worldwide, leading to an increase in cancer-related mortality. Early and accurate detection i…
POVQA: Preference-Optimized Video Question Answering with Rationales for Data Efficiency
Ashim Dahal, Ankit Ghimire, Saydul Akbar Murad +1
Long-video multimodal question answering requires structured reasoning over visual evidence and dialogue, but Large Vision-Language Models (LVLMs) are constrained by context-window…
Neural Network-based Study for Rice Leaf Disease Recognition and Classification: A Comparative Analysis Between Feature-based Model and Direct Imaging Model
Farida Siddiqi Prity, Mirza Raquib, Saydul Akbar Murad +3
Rice leaf diseases significantly reduce productivity and cause economic losses, highlighting the need for early detection to enable effective management and improve yields. This st…
Redemption Score: A Multi-Modal Evaluation Framework for Image Captioning via Distributional, Perceptual, and Linguistic Signal Triangulation
Ashim Dahal, Ankit Ghimire, Saydul Akbar Murad +1
Evaluating image captions requires cohesive assessment of both visual semantics and language pragmatics, which is often not entirely captured by most metrics. As such metrics incre…
EEG-to-Text Translation: A Model for Deciphering Human Brain Activity
Saydul Akbar Murad, Ashim Dahal, Nick Rahimi
With the rapid advancement of large language models like Gemini, GPT, and others, bridging the gap between the human brain and language processing has become an important area of f…
Embedding Shift Dissection on CLIP: Effects of Augmentations on VLM's Representation Learning
Ashim Dahal, Saydul Akbar Murad, Nick Rahimi
Understanding the representation shift on Vision Language Models like CLIP under different augmentations provides valuable insights on Mechanistic Interpretability. In this study,…
Multi-Lingual Cyber Threat Detection in Tweets/X Using ML, DL, and LLM: A Comparative Analysis
Saydul Akbar Murad, Ashim Dahal, Nick Rahimi
Cyber threat detection has become an important area of focus in today's digital age due to the growing spread of fake information and harmful content on social media platforms such…
Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification
Ashim Dahal, Saydul Akbar Murad, Nick Rahimi
Algorithmic level developments like Convolutional Neural Networks, transformers, attention mechanism, Retrieval Augmented Generation and so on have changed Artificial Intelligence.…
MpoxSLDNet: A Novel CNN Model for Detecting Monkeypox Lesions and Performance Comparison with Pre-trained Models
Fatema Jannat Dihan, Saydul Akbar Murad
Monkeypox virus (MPXV) is a zoonotic virus that poses a significant threat to public health, particularly in remote parts of Central and West Africa. Early detection of monkeypox l…
Unveiling Thoughts: A Review of Advancements in EEG Brain Signal Decoding into Text
Saydul Akbar Murad, Nick Rahimi
The conversion of brain activity into text using electroencephalography (EEG) has gained significant traction in recent years. Many researchers are working to develop new models to…
Impact Learning: A Learning Method from Features Impact and Competition
Nusrat Jahan Prottasha, Saydul Akbar Murad, Abu Jafar Md Muzahid +5
Machine learning is the study of computer algorithms that can automatically improve based on data and experience. Machine learning algorithms build a model from sample data, called…