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ORCIDMohammad Ali Zare Chahooki
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2020 – today
- 2024
[j14]Kia Jahanbin
, Mohammad Ali Zare Chahooki:
A Hybrid Deep Implicit Neural Model for Sentiment Analysis via Transfer Learning. IEEE Access 12: 131468-131486 (2024)- 2023
- [j13]Kia Jahanbin, Mohammad Ali Zare Chahooki:
Aspect-Based Sentiment Analysis of Twitter Influencers to Predict the Trend of Cryptocurrencies Based on Hybrid Deep Transfer Learning Models. IEEE Access 11: 121656-121670 (2023) - [j12]Seyedeh Zahra Sajadi, Seyed Mojtaba Sadjadi, Mohammad Ali Zare Chahooki:
AutoMF: A hybrid matrix factorization model with deep learning to select anti-viral drugs for Covid-19. J. Comput. Sci. 74: 102154 (2023) - 2022
- [c4]Motahareh Mohammad Rezai, Mohammad Ali Zare Chahooki:
Content-Based Telegram Group Recommender System. CSICC 2022: 1-6 - [c3]Motahareh Mohammad Rezai, Mohammad Ali Zare Chahooki:
Group recommendation in Telegram by membership graph analyzing. CSICC 2022: 1-7 - 2021
- [j11]Seyedeh Zahra Sajadi, Mohammad Ali Zare Chahooki, Sajjad Gharaghani, Karim Abbasi:
AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders. BMC Bioinform. 22(1): 204 (2021) - [c2]Davod Karimpour, Mohammad Ali Zare Chahooki, Ali Hashemi:
User recommendation based on Hybrid filtering in Telegram messenger. CSICC 2021: 1-7 - [c1]Davod Karimpour, Mohammad Ali Zare Chahooki, Ali Hashemi:
Telegram group recommendation based on users' migration. CSICC 2021: 1-6 - 2020
- [j10]Razieh Sheikhpour, Mehdi Agha Sarram, Sajjad Gharaghani, Mohammad Ali Zare Chahooki:
A robust graph-based semi-supervised sparse feature selection method. Inf. Sci. 531: 13-30 (2020)
2010 – 2019
- 2019
- [j9]Ali Hashemi, Mohammad Ali Zare Chahooki:
Telegram group quality measurement by user behavior analysis. Soc. Netw. Anal. Min. 9(1): 33:1-33:12 (2019) - 2017
- [j8]Razieh Sheikhpour, Mehdi Agha Sarram, Mohammad Ali Zare Chahooki, Robab Sheikhpour:
A kernelized non-parametric classifier based on feature ranking in anisotropic Gaussian kernel. Neurocomputing 267: 545-555 (2017) - [j7]Hamid Kargar Shooroki, Mohammad Ali Zare Chahooki:
Selection of effective training instances for scalable automatic image annotation. Multim. Tools Appl. 76(7): 9643-9666 (2017) - [j6]Razieh Sheikhpour, Mehdi Agha Sarram, Sajjad Gharaghani, Mohammad Ali Zare Chahooki:
A Survey on semi-supervised feature selection methods. Pattern Recognit. 64: 141-158 (2017) - 2016
- [j5]Mohammad Ali Zare Chahooki, Nasrollah Moghaddam Charkari:
Bridging the semantic gap for automatic image annotation by learning the manifold space. Comput. Syst. Sci. Eng. 31(1) (2016) - [i2]Malihe Mardanpour, Mohammad Ali Zare Chahooki:
Robust Hybrid Image Watermarking based on Discrete Wavelet and Shearlet Transforms. CoRR abs/1603.09396 (2016) - [i1]Seyed Hamid Reza Mohammadi, Mohammad Ali Zare Chahooki:
Web Spam Detection Using Multiple Kernels in Twin Support Vector Machine. CoRR abs/1605.02917 (2016) - 2015
- [j4]Mohammad Ali Zare Chahooki, Nasrollah Moghaddam Charkari:
Bridging the semantic gap for automatic image annotation by learning the manifold space. Comput. Syst. Sci. Eng. 30(4) (2015) - 2014
- [j3]Mohammad Ali Zare Chahooki, Nasrollah Moghaddam Charkari:
Shape classification by manifold learning in multiple observation spaces. Inf. Sci. 262: 46-61 (2014) - [j2]Mohammad Ali Zare Chahooki, Nasrollah Moghaddam Charkari:
Unsupervised manifold learning based on multiple feature spaces. Mach. Vis. Appl. 25(4): 1053-1065 (2014) - 2013
- [j1]Mohammad Ali Zare Chahooki, Nasrollah Moghaddam Charkari:
Learning the shape manifold to improve object recognition. Mach. Vis. Appl. 24(1): 33-46 (2013)
Coauthor Index
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