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A Comprehensive Survey on Convolutional Neural Networks .


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Convolutional Neural Networks (CNN) is a unique category of Neural Network that has displayed promising results in Computer Vision and Image Processing. Computer Vision problems heavily depend on the features of the input data and the process of extracting those features. CNN provides a novel way of extracting those features with the help of filters and automatically learning them. CNN‟s are also used in a broad spectrum of applications, including but not limited to Image Classification, Image Segmentation, Object Detection, Speech Recognition, and others. This paper focuses on the comprehensive analysis of CNN components, types of activation functions, regularization techniques, and a brief study of the different CNN architectures.

Keywords

Convolution Neural Network, GoogLeNet, ResNet, MobileNet.
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  • A Comprehensive Survey on Convolutional Neural Networks .

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Authors

C. Abhishek
no, India
Vineeta
no, India

Abstract


Convolutional Neural Networks (CNN) is a unique category of Neural Network that has displayed promising results in Computer Vision and Image Processing. Computer Vision problems heavily depend on the features of the input data and the process of extracting those features. CNN provides a novel way of extracting those features with the help of filters and automatically learning them. CNN‟s are also used in a broad spectrum of applications, including but not limited to Image Classification, Image Segmentation, Object Detection, Speech Recognition, and others. This paper focuses on the comprehensive analysis of CNN components, types of activation functions, regularization techniques, and a brief study of the different CNN architectures.

Keywords


Convolution Neural Network, GoogLeNet, ResNet, MobileNet.

References