This paper propose an improved method called the modified warm-up-free parallel window(PW) MAP decoding schemes to implement highly-parallel Turbo decoder architecture ... one for each constituent ...

One of the advancements is from data scientist Paril Ghori, who has effectively used an Autoencoder deep learning model to identify anomalies in residential furnaces. Utilizing cutting-edge machine ...

Recent advances in deep learning ... Decoder with Scale-Recursive Reconstructor (ConvED-SR) is proposed for SEEG speech decoding. ConvED-SR first extracts multiscale speech-related features from SEEG ...

SignBart is an efficient Isolated Sign Language Recognition model that decouples x and y coordinates using a lightweight encoder-decoder architecture. It achieves high accuracy with fewer than 750K ...

IBM says TerraMind is a multimodal model based on a novel “symmetric transformer-based encoder-decoder architecture ... machine learning experts, data scientists, and HPC engineers come ...

Abstract: In medical image segmentation, traditional fully supervised deep learning methods ... we design a Swin Transformer-based encoder-decoder architecture, Trans-AE-Unet, as the backbone for ...