A
Ali Heidari
Researcher at Islamic Azad University
Publications - 163
Citations - 2443
Ali Heidari is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Computer science & Benchmark (surveying). The author has an hindex of 15, co-authored 64 publications receiving 771 citations. Previous affiliations of Ali Heidari include Islamic Azad University, Isfahan & University of Tehran.
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INFO: An efficient optimization algorithm based on weighted mean of vectors
TL;DR: Info as mentioned in this paper is a modified weight mean method, whereby the weighted mean idea is employed for a solid structure and updating the vectors position using three core procedures: updating rule, vector combining, and a local search.
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A study of the mechanical properties of ground ceramic powder concrete incorporating nano-SiO2 particles
Ali Heidari,Davoud Tavakoli +1 more
TL;DR: In this article, the use of waste ground ceramic as a pozzolan in concrete was investigated and the results showed that adding ground ceramic up to 20% does not have a significantly negative effect on the compressive strength of concrete and that using any amount of ground ceramic in concrete reduces its water absorption capacity.
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Generative Adversarial Networks in Medical Image augmentation: A review
Yizhou Chen,Xu-Hua Yang,Zihan Wei,Ali Heidari,Nenggan Zheng,Zhicheng Li,Huiling Chen,Haigen Hu,Qianwei Zhou,Qiu Guan +9 more
TL;DR: A comprehensive and systematic review and analysis of medical image augmentation work are carried out, and its research status and development prospects are reviewed in this paper , which mainly collected by ELSEVIER, IEEE Xplore, and Springer from 2018 to 2021.
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Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation
Ailiang Qi,Dong Zhao,Fanhua Yu,Ali Heidari,Zongda Wu,Zhennao Cai,Fayadh Alenezi,Romany F. Mansour,Huiling Chen,Mayun Chen +9 more
TL;DR: Wang et al. as mentioned in this paper presented a new multilevel image segmentation method based on the swarm intelligence algorithm (SIA) to enhance the segmentation of COVID-19 X-rays.
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Multilevel threshold image segmentation for COVID-19 chest radiography: A framework using horizontal and vertical multiverse optimization
Hang Su,Dong Zhao,Hela Elmannai,Ali Heidari,Sami Bourouis,Zongda Wu,Zhennao Cai,Wenyong Gui,Mayun Chen +8 more
TL;DR: Wang et al. as mentioned in this paper proposed a multilevel thresholding image segmentation (MTIS) method based on an enhanced multiverse optimizer (CCMVO), which has a more assertive global search ability and can jump out of the local optimum in optimization.