An Empirical Model of Classifying Lung Affected Diseases to Detect COVID-19 Using Chest X-ray Employing Convolutional Neural Architecture. - Ovi Sarkar; Md. Robiul Islam 002; Tahmim Hossain; Md. Khalid Syfullah; Md. Tohidul Islam; Md. Moniruzzaman (IICAIET, 2022)

Plant Disease Classifier: Detection of Dual-Crop Diseases Using Lightweight 2D CNN Architecture. - Hasibul Islam Peyal; Md. Nahiduzzaman; Md. Abu Hanif Pramanik; Md. Khalid Syfullah; Saleh Mohammed Shahriar; Abida Sultana; Mominul Ahsan; Julfikar Haider; Amith Khandakar; Muhammad E. H. Chowdhury (IEEE Access, 2023)

IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation Techniques. - Md. Faysal Ahamed; Md. Khalid Syfullah; Ovi Sarkar; Md. Tohidul Islam; Md. Nahiduzzaman; Md. Rabiul Islam 001; Amith Khandakar; Mohamed Arselene Ayari; Muhammad E. H. Chowdhury (Sensors, 2023)

Parallel CNN-ELM: A multiclass classification of chest X-ray images to identify seventeen lung diseases including COVID-19. - Md. Nahiduzzaman; Md. Omaer Faruq Goni; Rakibul Hassan; Md. Robiul Islam 002; Md. Khalid Syfullah; Saleh Mohammed Shahriar; Md. Shamim Anower; Mominul Ahsan; Julfikar Haider; Marcin Kowalski (Expert Syst. Appl., 2023)

Bridging the gap: advancing the transparency and trustworthiness of network intrusion detection with explainable AI. - Md. Tohidul Islam; Md. Khalid Syfullah; Md. Golam Rashed; Dipankar Das 003 (Int. J. Mach. Learn. Cybern., 2024)