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Artificial Intelligence Based On Image Caption Generation

Artificial Intelligence is doing great progress in all factors, so automatically detecting the content of an image is a basic and important problem in AI fields that deals with computer sight and natural language processing. The paper is a study about the model based on a deep recurrent architecture that interacts with the recent advances in done in image captioning in computer sectors and machine translation fields and that can be used to produce natural sentences that gives detailed information of an image. Image captioning is a piece of work that requires the understanding of images and the awareness of producing correct description sentences with proper and suitable structure by extracting the features of image. In this study, we try to understand a hybrid system describing the use of Convolutional Neural Network (CNN) to generate an accurate description of the images and make the use of an LSTM to accurately arrange the meaningful sentences using the removed or extracted keywords. CNN checks the similarity in the target image with a large dataset of training images and tries to generate an accurate description using the trained captions.