Image Captioning Using Dl and Matlab

Abstract

This project seeks to create a system that produces captions for photos using MATLAB and Deep Learning methodologies, particularly Convolutional Neural Networks (CNN). The produced captions are then transformed into audio via a text-to-speech converter. The system also recognizes the primary subject in the picture and then plays an appropriate audio file (e.g., a barking sound for a dog) after the narration of the caption. This novel method improves the accessibility and engagement of visual material via the use of audio input, resulting in a more immersive experience. picture captioning refers to the process of generating descriptions for the content shown in a picture. Image captioning is used to give descriptions that contextualize the images. The examination of vast amounts of unlabeled photographs, the identification of obscure patterns for machine learning applications in autonomous vehicles, and the development of software that assists the visually impaired are only a few instances of the many domains where image captioning proves to be really advantageous. Deep learning models are applicable for picture captioning. Advancements in deep learning and natural language processing have facilitated the generation of descriptions for supplied images. This article will use neural networks for image captioning.