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ORCIDMd. Faysal Ahamed
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2020 – today
- 2024
[j6]Md. Faysal Ahamed
, Md. Rabiul Islam, Md. Nahiduzzaman, Md. Jawadul Karim, Mohamed Arselene Ayari, Amith Khandakar:
Automated Detection of Colorectal Polyp Utilizing Deep Learning Methods With Explainable AI. IEEE Access 12: 78074-78100 (2024)- [j5]Md. Faysal Ahamed, Md. Nahiduzzaman, Md. Rabiul Islam, Mansura Naznine, Mohamed Arselene Ayari, Amith Khandakar, Julfikar Haider:
Detection of various gastrointestinal tract diseases through a deep learning method with ensemble ELM and explainable AI. Expert Syst. Appl. 256: 124908 (2024) - [j4]Md. Faysal Ahamed, Md. Rabiul Islam, Md. Nahiduzzaman, Muhammad E. H. Chowdhury, Abdulrahman Alqahtani, M. Murugappan:
Automated Colorectal Polyps Detection from Endoscopic Images using MultiResUNet Framework with Attention Guided Segmentation. Hum. Centric Intell. Syst. 4(2): 299-315 (2024) - [j3]Md. Faysal Ahamed, Abdus Salam, Md. Nahiduzzaman, M. Abdullah-Al-Wadud, S. M. Riazul Islam:
Streamlining plant disease diagnosis with convolutional neural networks and edge devices. Neural Comput. Appl. 36(29): 18445-18477 (2024) - 2023
- [j2]Md. Faysal Ahamed, Md. Munawar Hossain, Md. Nahiduzzaman, Md. Rabiul Islam, Md. Robiul Islam, Mominul Ahsan, Julfikar Haider:
A review on brain tumor segmentation based on deep learning methods with federated learning techniques. Comput. Medical Imaging Graph. 110: 102313 (2023) - [j1]Md. Faysal Ahamed, Md. Khalid Syfullah, Ovi Sarkar, Md. Tohidul Islam, Md. Nahiduzzaman, Md. Rabiul Islam, Amith Khandakar, Mohamed Arselene Ayari, Muhammad E. H. Chowdhury:
IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation Techniques. Sensors 23(18): 7724 (2023) - [c2]Tahsin Tasnia Khan, Abid Hassan, Md. Faysal Ahamed, Samiul Islam:
Multi-label Bengali Abusive Comments Classification using Problem Transformation Method. CCE 2023: 1-6 - 2021
- [c1]Md. Faysal Ahamed, Syed Mahdi Mahi, Joyanta Mondal, Shovasis Kumar Biswas:
Low Cost Remotely Operated Underwater Vehicle. ICCCNT 2021: 1-6
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