This is a project focused on generating descriptive captions for images using a combination of Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs). This innovative approach leverages the power of CNNs for image feature extraction and LSTMs for generating contextually relevant captions, providing a seamless fusion of vision and natural language processing.
LSTM-CNN Fusion: Integrating LSTMs and CNNs to capitalize on their respective strengths for accurate and contextually rich image captions.
State-of-the-Art Models: Implementing cutting-edge deep learning models to ensure superior image feature extraction and caption generation.
Transfer Learning: Utilizing pre-trained CNN models for efficient feature extraction, allowing the model to generalize well to various types of images.
Provide an image as input, and witness the generation of descriptive captions using the trained LSTM-CNN model.
Train the model on your own dataset to adapt it to specific domains or image characteristics.