This work is an attempt to solve one of the most common problems of scene recognition. The dataset called PLACES2 was used for the purpose of experimentation which contains nearly 7 million labelled pictures of various scenes which is a sufficiently exhaustive dataset to train and test a model to get the desired output. The Convolutional Neural Network was used to design a neural architecture for our machine to store and classify the images as desired for the recognition of scene in the

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... Results strongly suggest that the trained model were able to perform successful scene recognition in the given data sample Abstract This work is an attempt to solve one of the most common problems of scene recognition. The dataset called PLACES2 was used for the purpose of experimentation which contains nearly 7 million labelled pictures of various scenes which is a sufficiently exhaustive dataset to train and test a model to get the desired output. The Convolutional Neural Network was used to design a neural architecture for our machine to store and classify the images as desired for the recognition of scene in the dataset. Results strongly suggest that the trained model were able to perform successful scene recognition in the given data sample