A Comparative Analysis of Attention Mechanism in RNN-LSTMs for Improved Image Captioning Performance

Image captioning which links computer vision with NATURAL LANGUAGE PROCESSING is critical in providing descriptions for the image. The proposed solution in this research is a hierarchical attention model which includes use of CNN features on images and LSTM networks with attention mechanisms for generating captions. By utilizing both object level and image level features, our method enhances the quality and relevance of captions, enhancing the variability of the automated image description.