Author(s)

Zirui Chen

Corresponding Author

Zirui Chen

Abstract

Convolutional Neural Networks (CNNs) have become pivotal in the deep learning field, garnering significant attention and rapid development in recent years. However, existing reviews often focus solely on applications without systematically addressing CNNs from a dimensional perspective. This paper categorizes CNNs by dimension to enhance their comprehensibility. We introduce the history of CNNs, explain various convolutional techniques, detail prominent models and their roles, and categorize CNNs by dimension, highlighting their applications accordingly. Additionally, we discuss existing challenges and propose future research directions, aiming to provide a comprehensive and systematic overview of CNNs.

Keywords

Computer vision (CV), convolutional neural networks (CNNs), deep learning, deep neural networks