Image Classification Using Convolutional Neural Network in Deep Learning
Synopsis
Image classification is a important problem of image processing in machine learning. In this image classification is done by using Deep Learning. In deep learning Convolutional Neural Network is used to classify the images with accurately. In CNN’s, networks of artificial neurons analyze large dataset to automatically images, sound, video and text. Convolutional Neural Network (CNN) become very popular for image classification in deep learning. CNN’s perform better than human subjects on many of the image classification datasets. A large number of different images, which contains types of Apple, Banana, Cactus, Avocado, Cherry are used for image classification. In image classification Relu activation function gives higher classification accuracy than other classifier and activation function. Keras and tensorflow libraries are used to classify images. By using CNN given input images should trained and using trained images to predict result of new classified images.
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