Abstract

The development of a deep learning-based image captioning system is the primary focus of this paper. In order for machines to comprehend and communicate the content of visual data, the aim of this paper is to generate descriptive textual captions for images. Convolutional neural networks (CNNs) for image feature extraction and recurrent neural networks (RNNs) for sequential language generation are utilized in the approach. Dataset collection, data preprocessing, CNN feature extraction, RNN-based captioning model implementation, model evaluation with metrics like BLEU score and METEOR, and results presentation are all included in the paper. An accessible image captioning system, extensive documentation, and a codebase that is well-documented are among the expected deliverables. Students learn about deep learning, computer vision, and natural language processing through this paper, which contributes to advancements in image comprehension and human-machine interaction with visual data The rolex replica UK best omega replica watches online with Swiss movements are worth having!
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