Automatic Image Captioning Using Deep Learning

Abstract

This study employs sophisticated Deep Learning techniques to develop a robust Automatic Image Captioning model, integrating Convolutional Neural Networks (CNNs) for intricate feature extraction and Long Short-Term Memory networks (LSTMs) for nuanced sequence generation. Aimed at addressing the surge in online visual content, the technology facilitates effective image interpretation with applications spanning accessibility enhancement for the visually impaired, improved content indexing for search capabilities, and heightened social media engagement through contextually relevant image captions. The research contributes valuable insights to computer vision, tackling challenges in generating coherent image descriptions. The meticulously tuned model undergoes both quantitative and qualitative evaluation, showcasing promising outcomes for innovative applications in content retrieval and human-computer interaction. Ultimately, this research aspires to advance automatic image understanding, promoting enhanced accessibility to visual information and propelling progress in artificial intelligence.