Abstract
Deep learning is a vital technique to implement artificial intelligence and a significant part of machine learning. In the last decades, deep learning gained enormous popularity due to the remarkable enhancement in computational ability and machine learning experimentation. The high computational time taken by the processes in deep learning because of large data sets can be compensated by increased computational ability. In deep learning, Convolutional Neural Network (CNN) or ConvNet is among the eminent approaches used for image classification. In recent image recognition competitions, CNN is outperforming other techniques of image classification. In this review paper, we have been discussed the basics of CNN, and significant developments in the history of CNN concerning image classification.
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Kumar, N., Kaur, N., Gupta, D. (2020). Major Convolutional Neural Networks in Image Classification: A Survey. In: Dutta, M., Krishna, C., Kumar, R., Kalra, M. (eds) Proceedings of International Conference on IoT Inclusive Life (ICIIL 2019), NITTTR Chandigarh, India. Lecture Notes in Networks and Systems, vol 116. Springer, Singapore. https://doi.org/10.1007/978-981-15-3020-3_23
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DOI: https://doi.org/10.1007/978-981-15-3020-3_23
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