Results 71 to 80 of about 30,189 (295)
Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks
CoRR, 2017 Recurrent Neural Networks (RNNs) continue to show outstanding performance in sequence modeling tasks. However, training RNNs on long sequences often face challenges like slow inference, vanishing gradients and difficulty in capturing long term dependencies.
Campos Camunez, Victor +4 more
openaire +5 more sources
Opt-RNN-DBFSVM: Optimal recurrent neural network density based fuzzy support vector machine
, 2023 Two major problems are encountered when using fuzzy SVM: (a) the number of local minima increases exponentially with the number of samples and (b) the quantity of required computer storage, required for a regular quadratic programming solver, increases ...
Abdellatif El Ouissari +1 more
core +1 more source
Personalized Network‐Guided Neuromodulation Enhances Human Working Memory
Advanced Science, EarlyView.A personalized neuromodulation framework combining individualized functional brain network targeting with real‐time neural decoding is introduced. Using concurrent TMS–fMRI, participant‐specific stimulation targets and optimal frequencies are identified. Only optimal‐frequency stimulation improves working memory across sessions.
Ahsan Khan +13 more
wiley +1 more source
Recurrent neural network (RNN).
, 2016 A trained RNN of excitatory and inhibitory rate units r(t) receives time-varying inputs u(t) and produces the desired time-varying outputs z(t). Inputs encode task-relevant sensory information or internal rules, while outputs indicate a decision in the ...
Guangyu R. Yang (2543947) +2 more
core +1 more source
Advanced Science, EarlyView.This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu +16 more
wiley +1 more source
Inhibitory Decay and Supercritical Brain Dynamics During Sleep Deprivation
Advanced Science, EarlyView.Sleep deprivation progressively shifts human brain dynamics from near‐critical toward supercritical states, as revealed by neuronal avalanche analysis of resting‐state fMRI. These changes track subjective sleep pressure rather than vigilance lapses and show marked network heterogeneity. A circuit model suggests that reduced inhibitory efficacy provides
Dai Zhang +6 more
wiley +1 more source
Applied Sciences, 2021 At the present time, power-system planning and management is facing the major challenge of integrating renewable energy resources (RESs) due to their intermittent nature.
Rehman Zafar +3 more
doaj +1 more source
Recurrent Neural Networks (RNNs): A gentle Introduction and Overview
CoRR, 2019 State-of-the-art solutions in the areas of "Language Modelling & Generating Text", "Speech Recognition", "Generating Image Descriptions" or "Video Tagging" have been using Recurrent Neural Networks as the foundation for their approaches. Understanding the underlying concepts is therefore of tremendous importance if we want to keep up with recent or
openaire +2 more sources
Advanced Science, EarlyView.This study presents printed magnetoresistive sensors with a vertically aligned architecture that enables high optical transparency and mechanical flexibility. By integrating deep learning for the analysis of complex spatiotemporal signal patterns, the system further achieves intelligent multimodal interaction capabilities.
Rui Xu +11 more
wiley +1 more source
Neural Machine Translation using Recurrent Neural Network
, 2020 In this era of globalization, it is quite likely to come across people or community who do not share the same language for communication as us. To acknowledge the problems caused by this, we have machine translation systems being developed. Developers of
Dhruv Mittal +3 more
core +1 more source