Zobrazeno 1 - 10
of 550
pro vyhledávání: '"AHMADI, MOHSEN"'
Artificial intelligence has dramatically reshaped our interaction with digital technologies, ushering in an era where advancements in AI algorithms and Large Language Models (LLMs) have natural language processing (NLP) systems like ChatGPT. This stu
Externí odkaz:
http://arxiv.org/abs/2406.06616
Autor:
Ahmadi, Mohsen, Nawaz, Muhammad Ali, Asadi, Hamed, Hemami, Mahmoud-Reza, Naderi, Morteza, Shafapourtehrany, Mahyat, Shabani, Farzin
Publikováno v:
Diversity and Distributions, 2024 May 01. 30(5), 1-15.
Externí odkaz:
https://www.jstor.org/stable/48769306
In the digital era, the integration of artificial intelligence (AI) in education has ushered in transformative changes, redefining teaching methodologies, curriculum planning, and student engagement. This review paper delves deep into the rapidly evo
Externí odkaz:
http://arxiv.org/abs/2309.02029
Autor:
Ahmadi, Mohsen, Nia, Masoumeh Farhadi, Asgarian, Sara, Danesh, Kasra, Irankhah, Elyas, Lonbar, Ahmad Gholizadeh, Sharifi, Abbas
In this study, the main objective is to develop an algorithm capable of identifying and delineating tumor regions in breast ultrasound (BUS) and mammographic images. The technique employs two advanced deep learning architectures, namely U-Net and pre
Externí odkaz:
http://arxiv.org/abs/2306.12510
Autor:
Nikpour, Maryam, Yousefi, Parisa Behvand, Jafarzadeh, Hadi, Danesh, Kasra, Shomali, Roya, Asadi, Saeed, Lonbar, Ahmad Gholizadeh, Ahmadi, Mohsen
This study confronts the growing challenges of energy consumption and the depletion of energy resources, particularly in the context of smart buildings. As the demand for energy increases alongside the necessity for efficient building maintenance, it
Externí odkaz:
http://arxiv.org/abs/2306.05567
Autor:
Ahmadi, Mohsen, Lonbar, Ahmad Gholizadeh, Nouri, Mohammadsadegh, Javidi, Amir Sharifzadeh, Beris, Ali Tarlani, Sharifi, Abbas, Salimi-Tarazouj, Ali
This study explores the use of a digital twin model and deep learning method to build a global terrain and altitude map based on USGS information. The goal is to artistically represent various landforms while incorporating precise elevation modificat
Externí odkaz:
http://arxiv.org/abs/2305.14460
Autor:
Ahmadi, Mohsen, Lonbar, Ahmad Gholizadeh, Naeini, Hajar Kazemi, Beris, Ali Tarlani, Nouri, Mohammadsadegh, Javidi, Amir Sharifzadeh, Sharifi, Abbas
This research assesses the performance of two deep learning models, SAM and U-Net, for detecting cracks in concrete structures. The results indicate that each model has its own strengths and limitations for detecting different types of cracks. Using
Externí odkaz:
http://arxiv.org/abs/2304.12600
Autor:
Reihanifar, Masoud, Takallou, Ali, Taheri, Mahyar, Gholizadeh Lonbar, Ahmad, Ahmadi, Mohsen, Sharifi, Abbas
Publikováno v:
In Groundwater for Sustainable Development November 2024 27
Publikováno v:
In Renewable and Sustainable Energy Reviews November 2024 205
Autor:
Nikpour, Maryam, Yousefi, Parisa Behvand, Jafarzadeh, Hadi, Danesh, Kasra, Shomali, Roya, Asadi, Saeed, Lonbar, Ahmad Gholizadeh, Ahmadi, Mohsen
Publikováno v:
In Journal of Network and Computer Applications March 2025 235