Zobrazeno 1 - 10
of 432 743
pro vyhledávání: '"Rahman, A. A."'
Autor:
Rahman, Md. Sohanur, Chowdhury, Muhammad E. H., Rahman, Hasib Ryan, Ahmed, Mosabber Uddin, Kabir, Muhammad Ashad, Roy, Sanjiban Sekhar, Sarmun, Rusab
In this study, we propose a novel and robust framework, Self-DenseMobileNet, designed to enhance the classification of nodules and non-nodules in chest radiographs (CXRs). Our approach integrates advanced image standardization and enhancement techniq
Externí odkaz:
http://arxiv.org/abs/2410.12584
Exterior painting of high-rise buildings is a challenging task. In our country, as well as in other countries of the world, this task is accomplished manually, which is risky and life-threatening for the workers. Researchers and industry experts are
Externí odkaz:
http://arxiv.org/abs/2409.05153
Autor:
Biswas, Amrijit, Hossain, Md. Ismail, Elahi, M M Lutfe, Cheraghian, Ali, Rahman, Fuad, Mohammed, Nabeel, Rahman, Shafin
A point cloud is a crucial geometric data structure utilized in numerous applications. The adoption of deep neural networks referred to as Point Cloud Neural Networks (PC- NNs), for processing 3D point clouds, has significantly advanced fields that r
Externí odkaz:
http://arxiv.org/abs/2408.14601
This study explores the concept of cross-disease transferability (XDT) in medical imaging, focusing on the potential of binary classifiers trained on one disease to perform zero-shot classification on another disease affecting the same organ. Utilizi
Externí odkaz:
http://arxiv.org/abs/2408.11493
Autor:
Kabir, Muhammad Rafsan, Sultan, Rafeed Mohammad, Asif, Ihsanul Haque, Ahad, Jawad Ibn, Rahman, Fuad, Amin, Mohammad Ruhul, Mohammed, Nabeel, Rahman, Shafin
Aligning large language models (LLMs) with a human reasoning approach ensures that LLMs produce morally correct and human-like decisions. Ethical concerns are raised because current models are prone to generating false positives and providing malicio
Externí odkaz:
http://arxiv.org/abs/2408.11879
Autor:
Ahmed, Nayeem, Rahman, Md Maruf, Ishrak, Md Fatin, Joy, Md Imran Kabir, Sabuj, Md Sanowar Hossain, Rahman, Md. Sadekur
This study compares eight pre-trained CNNs for diagnosing keratoconus, a degenerative eye disease. A carefully selected dataset of keratoconus, normal, and suspicious cases was used. The models tested include DenseNet121, EfficientNetB0, InceptionRes
Externí odkaz:
http://arxiv.org/abs/2408.09005
Autor:
Doddapaneni, Sumanth, Khan, Mohammed Safi Ur Rahman, Venkatesh, Dilip, Dabre, Raj, Kunchukuttan, Anoop, Khapra, Mitesh M.
Evaluating machine-generated text remains a significant challenge in NLP, especially for non-English languages. Current methodologies, including automated metrics, human assessments, and LLM-based evaluations, predominantly focus on English, revealin
Externí odkaz:
http://arxiv.org/abs/2410.13394
Autor:
Haider, Fabiha, Shifat, Fariha Tanjim, Ishmam, Md Farhan, Barua, Deeparghya Dutta, Sourove, Md Sakib Ul Rahman, Fahim, Md, Alam, Md Farhad
The proliferation of transliterated texts in digital spaces has emphasized the need for detecting and classifying hate speech in languages beyond English, particularly in low-resource languages. As online discourse can perpetuate discrimination based
Externí odkaz:
http://arxiv.org/abs/2410.13281
Inverse Synthetic Aperture Radar (ISAR) imaging presents a formidable challenge when it comes to small everyday objects due to their limited Radar Cross-Section (RCS) and the inherent resolution constraints of radar systems. Existing ISAR reconstruct
Externí odkaz:
http://arxiv.org/abs/2410.10085
Recent advancements in Artificial Intelligence (AI) algorithms have sparked a race to enhance hardware capabilities for accelerated task processing. While significant strides have been made, particularly in areas like computer vision, the progress of
Externí odkaz:
http://arxiv.org/abs/2410.09961