This repository demonstrates a simple autoencoder model for compressing and reconstructing images. The autoencoder is built using TensorFlow and Keras and is trained on a dataset of images to learn a ...

The proposed technique entails training an autoencoder on a substantial image dataset and subsequently employing it to compress new images by encoding them into a lower-dimensional representation, ...

In a new paper, University of Oxford researchers introduce a novel image compression approach that outperforms the JPEG standard at low bitrates, even without entropy coding or learning a distribution ...

The autoencoder managed to reduce the dimensions of the images to 15x15, which represents a used storage space of only 22% of the original space occupied by each original image. After the compression, ...