In an attempt to overcome these challenges, researchers from Google introduced “Sample What You Can’t Compress,” which couples autoencoder-based representation learning with diffusion models. This ...

1 Computer School, Hubei Polytechnic University, Huangshi, China 2 College of Computer Science, Huanggang Normal University, Huanggang, China This study aims to explore an autoencoder-based method for ...

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Memristor-based storage system with convolutional autoencoder-based image compression network Journal: Nature Communications Published: 2024-02-07 DOI: 10.1038/s41467-024-45312-0 Affiliations: 2 ...

Images occupy a prominent place in data because they are more visually appealing than sounds or texts. Acoustic waves are the only feasible alternative for long-distance underwater transmission since ...

Convolutional Neural Network (CNN) Image Compression - neuralnetwork-jpeg/Deep CNN Autoencoder - Image Compression copy.ipynb at master · sumn2u/neuralnetwork-jpeg ...

Secure transmission of images over a communication channel, with limited data transfer capacity, possesses compression and encryption schemes. A deep learning based hybrid image compression-encryption ...

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 ...