Abstract

Abstract: In recent years, deep learning has transformed computer vision, giving rise to automated image captioning systems bridging the gap between visual content and natural language. This paper presents an innovative approach to automated image captioning, combining deep learning models and methodologies. Our system employsConvolutional Neural Networks (CNNs) for robust image feature extraction and Recurrent Neural Networks (RNNs), specifically Long Short-Term Memory (LSTM) networks, for generating coherent captions. It is trained on diverse image-caption datasets, learning intricate associations between visual content and textual descriptions.

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