CNN Variants for Computer Vision: History, Architecture, Application, Challenges and Future Scope

Computer vision is becoming an increasingly trendy word in the area of image processing. The main contribution of this manuscript is in comparing various architectural evolutions in CNN by its architectural change, strengths, and weaknesses.

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• 1 With the emergence of computer vision applications, there is a significant demand to recognize objects automatically.
• 2 Deep CNN (convolution neural network) has benefited the computer vision community by producing excellent results in video processing, object recognition, picture classification and segmentation, natural language processing, speech recognition, and many other fields.
• 3 Additionally, the introduction of large amounts of data and readily available hardware has opened new avenues for CNN study.

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

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