Research Area: Machine Learning
In Artificial Intelligence (AI), the contents of an image are generated automatically which involves computer vision and NLP (Natural Language Processing). The neural model which is regenerative, is created. It depends on computer vision and machine translation. This model is used to generate natural sentences which eventually describes the image. This model consists of Convolutional Neural Network(CNN) as well as Recurrent Neural Network(RNN). The CNN is used for feature extraction from image and RNN is used for sentence generation. The model is trained in such a way that if input image is given to model it generates captions which nearly describes the image. The accuracy of model and smoothness or command of language model learns from image descriptions is tested on different datasets. These experiments show that model is frequently giving accurate descriptions for an input image.
Keywords:
Image Caption Generation
Deep Learning
Machine Learning
Deep Learning
Author(s) Name: Chetan Amritkar; Vaishali Jabade
Journal name:
Conferrence name: Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)
Publisher name: IEEE
DOI: 10.1109/ICCUBEA.2018.8697360
Volume Information:
