Convolutional Neural Networks (CNN)
image
caption
conventional methods
modern methods
hybrid
approach
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This study explores the challenges in Artificial
Intelligence (AI) systems in generating image captions, a task
that requires effective integration of computer vision and
natural language processing techniques. A comparative
analysis between traditional approaches such as retrieval-
based methods and linguistic templates) and modern
approaches based on deep learning such as encoder-decoder
models, attention mechanisms, and transformers).
Theoretical results show that modern models perform better
for the accuracy and the ability to generate more complex
descriptions, while traditional methods outperform speed
and simplicity. The paper proposes a hybrid framework that
combines the advantages of both approaches, where
conventional methods prod
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