A Deep Learning Model for Image Caption Generation - Naidu, P Aishwarya; Vats, Satvik; Anand, Gehna; V, Nalina (International Journal of Computer Sciences and Engineering, 2020)
Computer vision has been an area of interest for engineers and scientists who have been spearheading in the field of artificial intelligence from the late 1960s as it was very essential to give machines or robots the power of visualizing objects and activities around them like the human visual system. The ability to visualize 2-Dimensional images and extracting features from them can be utilised for developing various applications. The involvement of deep learning has been successful in bolstering the field of computer vision even further. The abundance of images in today's digital world and the amount of information contained in them have made them a very valuable and research worthy data item. A deep learning-based image caption generator model can incorporate the areas of natural language processing and computer vision with deep learning to give a solution in which the machine can extract features from an image and then describe those features in a natural language. Thus, explaining the contents of the image in a human-readable format. This model has various applications ranging from social causes like being an aid to visually impaired to enhancing search experience of users over the web. This paper analyses the various state-of-the-art work in the field of image processing, computer vision and deep learning and presents a deep learning model that generates captions describing the images given as input to the system.