Automatic System for Detecting Invasive Ductal Carcinoma Using Convolutional Neural Networks. - Md. Jamil-Ur Rahman; Rafi Ibn Sultan; Firoz Mahmud; Sazid Al Ahsan; Abdul Matin (TENCON, 2018)

An Efficient Machine Learning-Based Decision-Level Fusion Model to Predict Cardiovascular Disease. - Hafsa Binte Kibria; Abdul Matin (ICO, 2020)

A Comparative Study with Different Machine Learning Algorithms for Diabetes Disease Prediction. - Hafsa Binte Kibria; Abdul Matin; Nusrat Jahan; Sanzida Islam (CCE, 2021)

Hand Gesture Recognition Based Human Computer Interaction to Control Multiple Applications. - Sanzida Islam; Abdul Matin; Hafsa Binte Kibria (ICO, 2021)

Comparative analysis of two artificial intelligence based decision level fusion models for heart disease prediction. - Hafsa Binte Kibria; Abdul Matin; Sanzida Islam (ISIC, 2021)

CloudNet: A Deep Learning Approach for Mitigating Occlusions in Landsat-8 Imagery using Data Coalescence. - Paahuni Khandelwal; Samuel Armstrong; Abdul Matin; Shrideep Pallickara; Sangmi Lee Pallickara (e-Science, 2022)

Rapid Betweenness Centrality Estimates for Transportation Networks using Capsule Networks. - Abdul Matin; Samuel Armstrong; Saptashwa Mitra; Shrideep Pallickara; Sangmi Lee Pallickara (TransAI, 2022)

The severity prediction of the binary and multi-class cardiovascular disease - A machine learning-based fusion approach. - Hafsa Binte Kibria; Abdul Matin (Comput. Biol. Chem., 2022)

DISCERN: Leveraging Knowledge Distillation to Generate High Resolution Soil Moisture Estimation from Coarse Satellite Data. - Abdul Matin; Paahuni Khandelwal; Shrideep Pallickara; Sangmi Lee Pallickara (IEEE Big Data, 2023)

AIoT for sustainable manufacturing: Overview, challenges, and opportunities. - Abdul Matin; Md. Rafiqul Islam 004; Xianzhi Wang 001; Huan Huo; Guandong Xu (Internet Things, 2023)

Robust Multimodal Approach for Assembly Action Recognition. - Abdul Matin; Md Rafiqul Islam; Xianzhi Wang 001; Huan Huo (KES, 2024)

Accounting for Spatial Variability with the Histogram of Oriented Gradients Based Masking Improves Performance of Masked Autoencoder over Hyperspectral Satellite Imagery (Student Abstract). - Tanjim Bin Faruk; Abdul Matin; Shrideep Pallickara; Sangmi Lee Pallickara (AAAI, 2025)

TerraMAE: Learning Spatial-Spectral Representations from Hyperspectral Earth Observation Data via Adaptive Masked Autoencoders. - Tanjim Bin Faruk; Abdul Matin; Shrideep Pallickara; Sangmi Lee Pallickara (CoRR, 2025)

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss. - Abdul Matin; Tanjim Bin Faruk; Shrideep Pallickara; Sangmi Lee Pallickara (CoRR, 2025)