Abstract: The Convolutional Neural Network (CNN) is a frequently used algorithm used technique ... types of sparse data obtained via distinct pruning procedures. The design architecture outlined in ...

Abstract: This paper addresses the challenge of anti-jamming in orthogonal time frequency space (OTFS) modulation systems by proposing a novel anti-jamming decoder. The design of this decoder presents ...

The streaming encoder/decoder is a standalone device that converts one channel of SDI or HDMI to or from NDI HX formats. For users who need a 4Kp60 NDI HX encoder, it offers a configurable encoding ...

With the use of this dataset, we trained a bespoke Convolutional Neural Network (CNN) model, yielding testing, validation, and training accuracies of 89.50%, 92.53%, and 89.58%, respectively.

This paper introduces a compact end-to-end multi-branch convolutional neural network (CNN) architecture designed to decode brain signals from diverse modalities. The model integrates designated ...

Abstract: Scaling up Artificial Intelligence (AI) algorithms for massive datasets to improve their performance is becoming crucial. In Machine Translation (MT), one of most important research fields ...

Three modules, namely GMM, GFFRM and MFIM, are embedded in U-shaped encoder-decoder architecture to establish a novel RDH predictor GURNet. Extensive experiments implemented on four publicly available ...