Zobrazeno 1 - 10 of 22 pro vyhledávání: '"Adnan Firoze"'
1
Akademický článek
Machine learning for predicting landslide risk of Rohingya refugee camp infrastructure
Autor: Nahian Ahmed, Adnan Firoze, Rashedur M. Rahman
Publikováno v: Journal of Information and Telecommunication, Vol 4, Iss 2, Pp 175-198 (2020)
Since the dawn of human civilization, forced migration scenarios have been witnessed in different regions and populations, and is still present in the twenty-first century. The current largest population of stateless refugees in the world, the Rohing
Externí odkaz: https://doaj.org/article/f75aff01e90644d0b65409049bc6e70d
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2
Akademický článek
Fusion of BWM and AHP MCDM Methods to Choose the Most Suitable Secondary School for an Individual in the Context of Bangladesh
Autor: N. S. M. Rezaur Rahman, Md. Abdul Ahad Chowdhury, Adnan Firoze, Rashedur M. Rahman
Publikováno v: Vietnam Journal of Computer Science, Vol 6, Iss 3, Pp 311-328 (2019)
Choosing the best schools from a group of schools is a multi-criteria decision-making (MCDM) problem. In this paper, we have represented a method that uses the fusion of two multi-criteria decision-making methods, Best–Worst Method (BWM) and Analyt
Externí odkaz: https://doaj.org/article/f1c2d43259624b69abeda5bda912d4f0
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3
Akademický článek
An algorithmic approach to estimate cognitive aesthetics of images relative to ground truth of human psychology through a large user study
Autor: Tousif Osman, Shahreen Shahjahan Psyche, Tonmoay Deb, Adnan Firoze, Rashedur M. Rahman
Publikováno v: Journal of Information and Telecommunication, Vol 3, Iss 2, Pp 156-179 (2019)
This research introduces a learning model that estimates the cognitive perception of aesthetics. Taking psychology into account, this bridges the gap between human and machine. The goal is to build a machine-learning model that can estimate beauty in
Externí odkaz: https://doaj.org/article/fc96fee5e1c842e684d541f90a17bf32
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5
Machine learning for predicting landslide risk of Rohingya refugee camp infrastructure
Autor: Adnan Firoze, Rashedur M. Rahman, Nahian Ahmed
Publikováno v: Journal of Information and Telecommunication, Vol 4, Iss 2, Pp 175-198 (2020)
Since the dawn of human civilization, forced migration scenarios have been witnessed in different regions and populations, and is still present in the twenty-first century. The current largest population of stateless refugees in the world, the Rohing
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::848d127f7a0713ec21efeba0636cc431
https://doi.org/10.1080/24751839.2019.1704114
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8
Fusion of BWM and AHP MCDM Methods to Choose the Most Suitable Secondary School for an Individual in the Context of Bangladesh
Autor: Adnan Firoze, N. S. M. Rezaur Rahman, Rashedur M. Rahman, Md. Abdul Ahad Chowdhury
Publikováno v: Vietnam Journal of Computer Science, Vol 6, Iss 3, Pp 311-328 (2019)
Choosing the best schools from a group of schools is a multi-criteria decision-making (MCDM) problem. In this paper, we have represented a method that uses the fusion of two multi-criteria decision-making methods, Best–Worst Method (BWM) and Analyt
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::107db223e16b50db69cd393b5b945248
https://doi.org/10.1142/s2196888819500167
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9
CAE: Towards Crowd Anarchism Exploration
Autor: Adnan Firoze, Mohammad A. Khan, Mayamin Hamid Raha, Tonmoay Deb, Shahriar Ali Bijoy, Mahieyin Rahmun
Publikováno v: ICMLA
Towards effective violence detection in densely crowded scenes, we introduce two novel computationally inexpensive real time pipelines. One is for automatic crowd violence detection and another for capturing the region with highest crowd concentratio
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::437c30476f497d7d9755a22bc2a14e44
https://doi.org/10.1109/icmla51294.2020.00093
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10
Differential color harmony: A robust approach for extracting harmonic color features and perceiving aesthetics in a large image dataset
Autor: Adnan Firoze, Rashedur M. Rahman, Tonmoay Deb, Tousif Osman, Shahreen Shahjahan Psyche
This research work introduces and describes a robust method for extracting harmonic color features (HCFs) and verifies its validity by predicting visual aesthetics of a large image dataset against a large human survey on the same dataset. This work i
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::73f6ce2c3e5cd72d88da23dc88beb8f0
https://doi.org/10.1016/b978-0-12-819779-0.00001-0
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