With the extensive usage of Artificial Neural Networks in modern technologies, deep learning has advanced significantly. The development and acceptance of a particular neural network (NN) known as the convolutional neural networks is important in the context of deep learning (CNN or ConvNet). CNN is a type of feed-forward ANN that mostly analyses visual images. How to use CNN to create an image classifier is the issue that is being tackled here. This suggested research aims to provide a thorough understanding of CNN rather than treating it as a mystery. With the use of the Tensor Flow, Keras, and Theano deep learning packages, this work constructs a straightforward Multi Image Classification using CNN with a primary focus on CNN concepts. A dataset was used to train a CNN model that was created from scratch. There were also incorporated several loss functions for multi-image categorization.
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