Understanding Convolutional Neural Networks for Image Classification

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CNNs improve image classification accuracy significantly, surpassing classical models in many applications.
Advanced feature extraction in CNNs enables better performance across various domains, enhancing usability in real-world tasks.
The review covers the evolution of CNN architectures, focusing on their strengths while acknowledging inherent limitations.
Future applications of CNNs are promising, but ongoing research is needed to overcome emerging challenges and refine frameworks.

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Review highlights strengths and limitations of CNNs in image classification, suggesting future advancements.

Jinghan Xu (2025) studied this question.

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