GitHub

Pytorch implementation for image compression and reconstruction via autoencoder

This is an autoencoder with cylic loss and coding parsing loss for image compression and reconstruction. Network backbone is simple 3-layer fully conv (encoder) and symmetrical for decoder. Finally it ...
IEEE

Autoencoder Architectures for Low-Rate Sparse Point Cloud Geometry Coding

Abstract: Efficient compression of sparse point cloud geometry remains a critical challenge in 3D content processing, particularly for low-rate scenarios where conventional codecs struggle to maintain ...
IEEE

Performance Evaluation of Autoencoder for Coding and Modulation in Wireless Communications

Abstract: The end-to-end autoencoder is a novel and attracting concept to innovate communication system architecture. In its training stage, the end-to-end autoencoder needs differentiable channel ...
EconoTimes

OmniComm Systems Introduces AutoEncoder, an Innovative, Coding Solution for Clinical Trials

Fort Lauderdale, FL, May 07, 2018 -- OmniComm Systems, Inc. (OTCQX: OMCM), a leading global provider of clinical data management technology, today announced the launch of OmniComm AutoEncoder, a ...
Business Insider

OmniComm Systems Introduces AutoEncoder, an Innovative, Coding Solution for Clinical TrialsAutoEncoder to Make Global Debut at Industry Events in Europe, North America and China

Fort Lauderdale, FL, May 07, 2018 (GLOBE NEWSWIRE) -- OmniComm Systems, Inc. (OTCQX: OMCM), a leading global provider of clinical data management technology, today announced the launch of OmniComm ...
GitHub

Lesson No. 3: Variational autoencoder code for CelebA dataset takes too long to load

train_data = utils.image_dataset_from_directory( "celeba-dataset/img_align_celeba/img_align_celeba", labels = None, color_mode="rgb", image_size = (64, 64), batch ...