Zobrazeno 1 - 10
of 5 008
pro vyhledávání: '"Siam, A"'
Our everyday lives now heavily rely on artificial intelligence (AI) powered large language models (LLMs). Like regular users, programmers are also benefiting from the newest large language models. In response to the critical role that AI models play
Externí odkaz:
http://arxiv.org/abs/2411.09224
Autor:
Siam, Mennatullah
There have been works discussing the adoption of a human rights framework for responsible AI, emphasizing various rights such as the right to contribute to scientific advancements. Yet, to the best of our knowledge, this is the first attempt to take
Externí odkaz:
http://arxiv.org/abs/2410.22963
Autor:
Siam, Shakhrul Iman, Ahn, Hyunho, Liu, Li, Alam, Samiul, Shen, Hui, Cao, Zhichao, Shroff, Ness, Krishnamachari, Bhaskar, Srivastava, Mani, Zhang, Mi
Publikováno v:
ACM Trans. Sen. Netw.(August 2024)
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we provide a systematic and comprehensive review of AIoT r
Externí odkaz:
http://arxiv.org/abs/2410.19998
Autor:
Alamu, Opeyemi Sheu, Choque, Bismar Jorge Gutierrez, Rizvi, Syed Wajeeh Abbs, Hammed, Samah Badr, Medani, Isameldin Elamin, Siam, Md Kamrul, Tahir, Waqar Ahmad
Breast cancer remains a significant global health challenge, with prognosis and treatment decisions largely dependent on clinical characteristics. Accurate prediction of patient outcomes is crucial for personalized treatment strategies. This study em
Externí odkaz:
http://arxiv.org/abs/2410.13404
Autor:
Alamu, Opeyemi Sheu, Siam, Md Kamrul
Publikováno v:
Journal of Intelligent Learning Systems and Applications, Vol.16, No.4, 2024
A comparative analysis of deep learning models and traditional statistical methods for stock price prediction uses data from the Nigerian stock exchange. Historical data, including daily prices and trading volumes, are employed to implement models su
Externí odkaz:
http://arxiv.org/abs/2410.07220
Autor:
Broni-Bediako, Clifford, Xia, Junshi, Song, Jian, Chen, Hongruixuan, Siam, Mennatullah, Yokoya, Naoto
Learning with limited labelled data is a challenging problem in various applications, including remote sensing. Few-shot semantic segmentation is one approach that can encourage deep learning models to learn from few labelled examples for novel class
Externí odkaz:
http://arxiv.org/abs/2409.11227
Autor:
Dip, Muhammad Sudipto Siam, Hasan, Md Anik, Bipro, Sapnil Sarker, Raiyan, Md Abdur, Motin, Mohammod Abdul
In this study, we address the challenge of speaker recognition using a novel data augmentation technique of adding noise to enrollment files. This technique efficiently aligns the sources of test and enrollment files, enhancing comparability. Various
Externí odkaz:
http://arxiv.org/abs/2409.10240
Publikováno v:
Accounting, Pp 119-126 (2021)
The study aimed to identify the impact of the credit query in reducing credit risks from the viewpoint of workers in Jordanian banks, and to achieve the goal of the study, the researchers adopted the descriptive analytical approach, where a questionn
Externí odkaz:
https://doaj.org/article/02921558e25147b2b0b3894914cef8ba
This research is based on the present missile detection technologies in the world and the analysis of these technologies to find a cost effective solution to implement the system in Bangladesh. The paper will give an idea of the missile detection tec
Externí odkaz:
http://arxiv.org/abs/2407.07452
Machine learning (ML) applied to routine patient monitoring within intensive care units (ICUs) has the potential to improve care by providing clinicians with novel insights into each patient's health and expected response to interventions. This paper
Externí odkaz:
http://arxiv.org/abs/2406.16915