Abstract
With the advent of technologies, real-time data is essentially required for future development. Everyday, a huge amount of visual data is being collected, but to use it efficiently, we need to recognize, understand and arrange the visual data for a perfect approach. So, the neural network was introduced to find out patterns from images, a form of visual data as the neuron functionality in a human brain. It is biologically inspired programming approach to allow the machine to learn from observational data. Neural networks have provided solutions to several problems of image recognition, and it is actively utilized in the medical field due to its efficiency. This paper concentrates upon the use of RNN and CNN in the feature extraction of images and the challenges. The paper also presents a brief literature review of the neural networks like CNN and RNN.
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Dhruv, P., Naskar, S. (2020). Image Classification Using Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN): A Review. In: Swain, D., Pattnaik, P., Gupta, P. (eds) Machine Learning and Information Processing. Advances in Intelligent Systems and Computing, vol 1101. Springer, Singapore. https://doi.org/10.1007/978-981-15-1884-3_34
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