Abstract
Abstract: This paper focuses on developing an image captioning system using deep learning techniques. The paper aims to generate descriptive textual captions for images, enabling machines to understand and communicate the content of visual data. The methodology involves leveraging convolutional neural networks (CNNs) for image feature extraction and recurrent neural networks (RNNs) for sequential language generation. The paper includes steps such as dataset collection, data preprocessing, CNN feature extraction, RNN-based captioning model implementation, model evaluation using metrics like BLEU score and METEOR, and presenting the results obtained. The expected deliverables include a functional image captioning system, comprehensive documentation, and a well-documented codebase. Through this paper, students gain practical experience in deep learning, computer vision, and natural language processing, contributing to advancements in image understanding and humanmachine interaction with visual data
Published Version
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