Convolution Neural Network Based Image Recognition

Sofia Hamid, Mrigana Walia

Abstract: The identification of an image is one thorny task in computer vision problems. Using the python programming language and a few other machine learning algorithms and python libraries, this image recognition and feature extraction can be achieved. In pattern- and image-recognition problems, convolutionary neural networks (CNNs) are commonly used as they have a range of benefits compared to other techniques. The basics of CNNs are covered in this document, including a description of the different layers used. In this paper, we presented a model for cat and dog image recognition from the Convolutionary Neural Network (CNN). Before feeding it to the CNN model, the cat and dog dataset is pre-processed.

Keywords: Image processing, pooling layer, convolutional layer, Deep Learning, Tensor flow etc

How to Cite?: Sofia Hamid, Mrigana Walia, "Convolution Neural Network Based Image Recognition", Volume 10 Issue 2, February 2021, International Journal of Science and Research (IJSR), Pages: 1673-1677, https://www.ijsr.net/getabstract.php?paperid=SR21225214136, DOI: https://dx.doi.org/10.21275/SR21225214136

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