A review of convolutional neural networks in computer vision

Abstract In computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super-resolution reconstruction with the rapid development of deep convolutional neural network (CNN). On this basis, this paper gives a comprehensive overview of the past and current research status of the applications of CNN models in computer vision fields, e.g., image classification, object detection, and video predicti...

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• 1 The CNN has superior features for autonomous learning and expression, and feature extraction from original input data can be realized by means of training CNN models that match practical applications.
• 2 Due to the rapid progress in deep learning technology, the structure of CNN is becoming more and more complex and diverse.
• 3 Consequently, it gradually replaces the traditional machine learning methods.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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