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:: Volume 16, Issue 1 (3-2025) ::
IJOR 2025, 16(1): 147-158 Back to browse issues page
IQ estimation from MRI images using GCNN model
Sara Motamed * , Mahboubeh Yaghoubi
Department of Computer Engineering, Fouman and Shaft Branch, Islamic Azad University, Fouman, Iran , sara.motamed@iau.ac.ir
Abstract:   (5 Views)

Intelligence has long been an interesting and important topic in psychology and cognitive science. IQ is considered a basic measure of a person's cognitive abilities, which includes various aspects of reasoning, problem solving, memory, and overall intellectual ability. Considering the importance of IQ in cognitive and psychological evaluations, the main goal of this article was to provide a new and effective approach to improve the accuracy of estimating this measure through complex brain data processing. In this paper, we have analyzed and developed a hybrid model of GWO algorithm and CNN (GCNN) in order to estimate IQ using brain MRI images. The results of the experiments showed that the accuracy of the proposed model was significantly better than the traditional techniques, and this indicates the high capabilities of the model in interpreting complex medical data. By examining the results, we find that the accuracy of the proposed model with an estimation rate of 93.10% is better than other competing methods.

Keywords: IQ, Deep learning, Brain MRI images, Grey Wolf Optimization (GWO) algorithm, Convolutional neural network (CNN).
Full-Text [PDF 546 kb]   (5 Downloads)    
Type of Study: Original | Subject: Other
Received: 2025/03/19 | Accepted: 2025/10/21 | Published: 2025/10/21
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 16, Issue 1 (3-2025) Back to browse issues page
مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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