JOURNAL ARTICLE

Image caption generation

Kusa AnjanaM. Swetha

Year: 2025 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

ABSTRACT Image caption generation is a multidisciplinary task at the intersection of computer vision and natural language processing, which aims to automatically produce descriptive and coherent textual descriptions for given images. This process involves extracting meaningful visual features from images using techniques such as convolutional neural networks (CNNs), followed by generating relevant captions through language models, often utilizing recurrent neural networks (RNNs) or transformer architectures. Image captioning has significant applications in accessibility for visually impaired individuals, image retrieval, and content summarization. Recent advances leverage attention mechanisms and large-scale datasets to improve the accuracy and contextual relevance of generated captions, making the technology increasingly effective in understanding and describing complex visual scenes.. Keywords: Deep learning, Image Caption Generation, Visual Features, Attention Mechanism, Descriptive Text, , Large-scale Datasets, Contextual Relevance..

Keywords:
Closed captioning Convolutional neural network Natural language Leverage (statistics) Image (mathematics) Relevance (law) Visualization Image processing

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Topics

Multimodal Machine Learning Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Artificial Intelligence Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Generative Adversarial Networks and Image Synthesis
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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