Zobrazeno 1 - 10
of 826
pro vyhledávání: '"Kabir, Muhammad A."'
Sentence-level embedding is essential for various tasks that require understanding natural language. Many studies have explored such embeddings for high-resource languages like English. However, low-resource languages like Bengali (a language spoken
Externí odkaz:
http://arxiv.org/abs/2411.15270
As the use of web browsers continues to grow, the potential for cybercrime and web-related criminal activities also increases. Digital forensic investigators must understand how different browsers function and the critical areas to consider during we
Externí odkaz:
http://arxiv.org/abs/2410.12605
Artificial intelligence (AI) has emerged as a promising tool for predicting COVID-19 from medical images. In this paper, we propose a novel continual learning-based approach and present the design and implementation of a mobile application for screen
Externí odkaz:
http://arxiv.org/abs/2410.12589
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
Analysis of child development facts and myths using text mining techniques and classification models
Publikováno v:
Heliyon, 2024, 10 (17)
The rapid dissemination of misinformation on the internet complicates the decision-making process for individuals seeking reliable information, particularly parents researching child development topics. This misinformation can lead to adverse consequ
Externí odkaz:
http://arxiv.org/abs/2408.13091
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
Publikováno v:
Heliyon, 2024, 10 (17)
Assistive technologies have been developed to enhance blind users' typing performance, focusing on speed, accuracy, and effort reduction. One such technology is word prediction software, designed to minimize keystrokes required for text input. This s
Externí odkaz:
http://arxiv.org/abs/2408.10791
Autor:
Islam, Sheikh Mohammed Shariful, Abrar, Moloud, Tegegne, Teketo, Loranjo, Liliana, Karmakar, Chandan, Awal, Md Abdul, Hossain, Md. Shahadat, Kabir, Muhammad Ashad, Mahmud, Mufti, Khosravi, Abbas, Siopis, George, Moses, Jeban C, Maddison, Ralph
Machine learning models have the potential to identify cardiovascular diseases (CVDs) early and accurately in primary healthcare settings, which is crucial for delivering timely treatment and management. Although population-based CVD risk models have
Externí odkaz:
http://arxiv.org/abs/2407.16721
Publikováno v:
Heliyon, 2024, 10 (14)
The COVID-19 pandemic has had adverse effects on both physical and mental health. During this pandemic, numerous studies have focused on gaining insights into health-related perspectives from social media. In this study, our primary objective is to d
Externí odkaz:
http://arxiv.org/abs/2402.09897
Data-driven advances have resulted in significant improvements in dairy production. However, the meat industry has lagged behind in adopting data-driven approaches, underscoring the crucial need for data standardisation to facilitate seamless data tr
Externí odkaz:
http://arxiv.org/abs/2310.17684