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Convolutional Neural Network and its Architectures

Radhey Shyam

Abstract


Convolutional neural network (CNN) is a type of artificial neural network (ANN) with multiple layers. From the past decades, it has been considered as a powerful classification technique as it can handle a huge amount of imagery data. It can be applied in the field of image recognition. The name CNN has been derived from the mathematical linear operation known as convolution which is performed between two matrices. CNN has multiple building blocks, for instance, convolution layers, non-linearity layers, pooling layers, and flattening followed by fully connected layers. The CNN has better performance in the machine learning applications. Particularly, the domains that use imagery data, such as computer vision, natural language processing, medical diagnosis, and robotics. This research work will present deeper insights of CNN. Furthermore, it will also highlight the parameters that are influencing its efficacy.

Keywords


Artificial neural network, convolutional neural network, machine learning, deep learning, computer vision

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References


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