Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Sajib Ahmed"'
Autor:
Nazia Khatun, Sajib Ahmed, Mohammad Sajjad Hossain, Syed Farid Uddin Farhad, Md Al- Mamun, Mohammad Saiful Alam, Most. Hosney Ara Begum, Nazmul Islam Tanvir, Mahmuda Hakim, Suravi Islam
Publikováno v:
Heliyon, Vol 9, Iss 2, Pp e13019- (2023)
In the current study, nanocrystalline CoY0.5xLa0.5xFe2-xO4 (where x = 0.00, 0.02, 0.04, 0.06, 0.08, and 0.10) ferrites have been synthesized via a sol-gel auto combustion process. The synthesized powders were pressed into pellet forms and sintered at
Externí odkaz:
https://doaj.org/article/6083ab1f9fc54bac83e844857a26750f
Publikováno v:
2022 IEEE International Conference on Power and Energy (PECon).
Autor:
Nazia Khatun, Sajib Ahmed, Mohammad Sajjad Hossain, Syed Farid Uddin Farhad, Md Al- Mamun, Mohammad Saiful Alam, Most. Hosney Ara Begum, Nazmul Islam Tanvir, Mahmuda Hakim, Suravi Islam
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
2021 9th International Renewable and Sustainable Energy Conference (IRSEC).
Publikováno v:
2021 4th International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE).
Publikováno v:
Sustainable Energy Technologies and Assessments. 53:102390
Publikováno v:
Journal of Automation, Mobile Robotics and Intelligent Systems. :74-80
Autor:
Jahid Siraz Chowdhury, Kumarashwaran Vadevelu, A.F.M. Zakaria, Abdullah Al-Mamun, Sajib Ahmed
In the complex landscape of educational philosophy and policy, a difficult challenge arises — the entwined issues of racism and other demographic differences, and evolving education policies. Traditional historical accounts fall short of addressing
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030180577
For mammogram image analysis, feature extraction is the most crucial step when machine learning techniques are applied. In this paper, we propose RMID (Radon-based Multi-resolution Image Descriptor), a novel image descriptor for mammogram mass classi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96482837d41f0a967dd63ff01701f986
https://doi.org/10.1007/978-3-030-18058-4_18
https://doi.org/10.1007/978-3-030-18058-4_18
Publikováno v:
Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications ISBN: 9783030208042
CompIMAGE
CompIMAGE
Mammogram images are broadly categorized into two types: carniocaudal (CC) view and mediolateral oblique (MLO) view. In this paper, we study the effect of different image views for mammogram mass classification. For the experiments, we consider a dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f4023068308c59d85cd232559b0c009e
https://doi.org/10.1007/978-3-030-20805-9_14
https://doi.org/10.1007/978-3-030-20805-9_14