TVBEurope

A codec revolution

Could pure AI encoding reinvent compression and make traditional codecs obsolete? Monica Heck examines what the future might ...
IEEE

Encoder-Decoder Based Deep Reinforcement Learning for Multi-AUV Assisted Data Collection in ...

Abstract: Reliable and timely data collection poses a significant challenge for underwater wireless sensor networks (UWSNs), primarily due to the extremely low data rate of underwater communication ...
IEEE

Deep Learning-Based Iterative Residual Encoder-Decoder Solution for Electromagnetic ...

Abstract: In this letter, we propose a deep learning-based iterative residual encoder-decoder method (IRED), which provides an efficient deep learning framework for electromagnetic modeling over a ...
GitHub

PtychoNN: Deep learning of ptychographic imaging

PtychoNN is a two-headed encoder-decoder network that simultaneously predicts sample amplitude and phase from input diffraction data alone. PtychoNN is 100s of times faster than iterative phase ...
marktechpost

Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder ...

CNNs are specialized deep neural networks for processing data with a grid-like topology, such as images. A CNN automatically detects the important features without any human supervision. They are ...
Scientific Research Publishing

End-to-End Auto-Encoder System for Deep Residual Shrinkage Network for AWGN Channels ()

1 School of Mathematical Sciences, Guizhou Normal University, Guiyang, China. 2 School of Big Data and Computer Science, Guizhou Normal University, Guiyang, China. With the rapid development of deep ...
C&EN

Fragment Linker Prediction Using the Deep Encoder-Decoder Network for PROTACs Drug Design

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. A drug discovery and development pipeline is a prolonged and complex process that ...