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 ...

In medical image processing compression is required to reduce the bandwidth and storage related issues. In this method DCT and Autoencoder based image compression technique is used for the better ...

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, ...