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All Journal Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Journal of Information Technology and Computer Engineering International Journal of Artificial Intelligence and Robotics (IJAIR) International Journal of Research and Applied Technology (INJURATECH) Jurnal Ilmiah Computer Science
Mohammed, Ayaz Khalid
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Aerospace Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Journal : Jurnal Ilmiah Computer Science

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Advancements and Applications of Convolutional Neural Networks in Image Analysis: A Comprehensive Review Majeed Zangana, Hewa; Mohammed, Ayaz Khalid; Mustafa, Firas Mahmood
Jurnal Ilmiah Computer Science Vol. 3 No. 1 (2024): Volume 3 Number 1 July 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jics.v3i1.30

Abstract

Convolutional Neural Networks (CNNs) have revolutionized image analysis, extracting meaningful features from raw pixel data for accurate predictions. This paper reviews CNN fundamentals, architectures, training methods, applications, challenges, and future directions. It introduces CNN basics, including convolutional and pooling layers, and discusses diverse architectures like LeNet, AlexNet, ResNet, and DenseNet. Training strategies such as data preprocessing, initialization, optimization, and regularization are explored for improved performance and stability. CNN applications span healthcare, agriculture, ecology, remote sensing, and security, enabling tasks like object detection, classification, and segmentation. However, challenges like interpretability, data bias, and adversarial attacks persist. Future research aims to enhance CNN robustness, scalability, and ethical deployment. In conclusion, CNNs drive transformative advancements in image analysis, with ongoing efforts to address challenges and shape the future of AI-enabled technologies.
Co-Authors Mahmood Mustafa, Firas Majeed Zangana, Hewa Mustafa , Firas Mahmood Mustafa, Firas Mahmood Omar , Marwan Omar, Naaman Sallow, Amira Bibo Sallow, Zina Bibo Zangana, Hewa Majeed Zeebaree, Subhi R. M.