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Found 8 papers, 0 papers with code
Laplacian-guided Entropy Model in Neural Codec with Blur-dissipated Synthesis
The global spatial context is built upon the Transformer, which is specifically designed for image compression tasks.
Neural-based Compression Scheme for Solar Image Data
In this work, we propose an adversarially trained neural network, equipped with local and non-local attention modules to capture both the local and global structure of the image resulting in a better trade-off in rate-distortion (RD) compared to conventional hand-engineered codecs.
Dynamic Changes of Brain Network during Epileptic Seizure
Epilepsy is a neurological disorder identified by sudden and recurrent seizures, which are believed to be accompanied by distinct changes in brain dynamics.
Multi-Context Dual Hyper-Prior Neural Image Compression
In addition, we introduce a novel entropy model that incorporates two different hyperpriors to model cross-channel and spatial dependencies of the latent representation.
Multi-spectral Entropy Constrained Neural Compression of Solar Imagery
Recently successful end-to-end optimized neural network-based image compression systems have shown great potential to be used in an ad-hoc manner.
Context-Aware Neural Video Compression on Solar Dynamics Observatory
NASA's Solar Dynamics Observatory (SDO) mission collects large data volumes of the Sun's daily activity.
Frequency Disentangled Features in Neural Image Compression
The design of a neural image compression network is governed by how well the entropy model matches the true distribution of the latent code.
Attention-Based Generative Neural Image Compression on Solar Dynamics Observatory
We have designed an ad-hoc ANN-based image compression scheme to reduce the amount of data needed to be stored and retrieved on space missions studying solar dynamics.
