Image Caption Generator Using Deep Learning

This project introduces a deep learning based image caption generator, merging computer vision and natural language processing. Leveraging pre-trained convolutional neural networks (CNNs) like InceptionV3 and recurrent neural networks (RNNs), the model extracts image features and generates coherent captions. Using datasets like MS COCO, the system is trained to map image features to corresponding captions. The model architecture incorporates beddings, LSTM layers, and dense layers, optimizing parameters with categorical cross-entropy loss during training. There sulting model can generate meaningful captions for new images, showcasing the synergy between visual understanding and language generation in the realm of multimedia applications. The proposed image caption generator shows the fusion of computer vision and natural language processing capabilities. Using deep learning techniques, specifically pre-trained CNNs andRNNs, allows for the creation of a model capable of generating contextually relevant captions for a diverse range of images.This work contributes to the evolving landscape of multimedia applications, showcasing the potential of deep learning in understanding and generating human like descriptions of visual content.