Open AccessEmployability of Neural Network Tools and Techniques for Enhancing Image Caption Generation
Author(s) -
Harshit Dua
Publication year - 2020
Publication title -
international journal of research in science and technology(online)/international journal of research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2454-180X
pISSN - 2249-0604
DOI - 10.37648/ijrst.v10i04.003
Subject(s) - computer science , convolutional neural network , artificial intelligence , plan (archaeology) , set (abstract data type) , presentation (obstetrics) , image (mathematics) , artificial neural network , subtitle , computer vision , natural language processing , programming language , medicine , archaeology , radiology , history , operating system
Nowadays, there is massive research in generating automatic image caption; this technique is very challenging and uses Natural language processing. For instance, it could assist incapacitated people with improving the matter of images on the web. Likewise, it could give more precise and minimized images/recordings in situations, such as picture sharing in interpersonal organization or video surveillance system. The structure comprises a convolutional neural organization (CNN) traced by a repetitive neural organization (RNN). The strategy can produce picture sayings that are generally semantically unmistakable and linguistically right by taking in information from picture and subtitle matches. Individuals, for the most part, depict a scene utilizing characteristic languages which are concise and reduced. However, computer vision frameworks define the set by taking a picture which is a two-measurement presentation. The plan is to picture and engrave similar places and projects from the image to the sentences.