المؤلفون: Boonrawd, Pudsadee, Phonyiam, Korawat

المصدر: 2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C), 2022. :199-204 Aug, 2022

Relation: 2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)

المؤلفون: M.M. Vijay, Om Prakash Kumar, Sharmila Anand John Francis, Allwin Devaraj Stalin, Shweta Vincent

المصدر: Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 4, Pp 102033- (2024)

مصطلحات موضوعية: Machine learning, Recurrent neural network, CNTFET 32 nm technology, MVL, RNN-LSTM, SDG 7, Electronic computers. Computer science, QA75.5-76.95

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1319157824001228; https://doaj.org/toc/1319-1578

URL الوصول: https://doaj.org/article/4dd14dfa007b48be87495a0aadb1a66e

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المؤلفون: Ahmad Yoosofan, Falah Obaid, Amin Babadi

المساهمون: University of Kashan, Department of Computer Science, Aalto-yliopisto, Aalto University

المصدر: Applied Computer Systems, Vol 25, Iss 1, Pp 57-61 (2020)

مصطلحات موضوعية: Computer science, 02 engineering and technology, computer vision (cv), convolutional neural network (cnn), QA76.75-76.765, Deep Learning, recurrent neural network with long short-term memory (rnn-lstm), 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Computer software, Project management, 050210 logistics & transportation, Signal processing, business.industry, Deep learning, 05 social sciences, Software development, deep learning, Information technology, General Medicine, Hand Gesture Recognition (HGR), Recurrent Neural Network with Long Short-Term Memory (RNN-LSTM), Convolutional Neural Network (CNN), hand gesture recognition (hgr), Recurrent neural network, Gesture recognition, 020201 artificial intelligence & image processing, Applications of artificial intelligence, Artificial intelligence, Computer Vision (CV), business

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5944d356610c0debf3316b143ea54c8c
https://doi.org/10.2478/acss-2020-0007

المؤلفون: Serge P. Hoogendoorn, Dorine C. Duives, Tim P. van Oijen

المصدر: Sensors, 20(21)
Sensors
Volume 20
Issue 21
Sensors, Vol 20, Iss 6032, p 6032 (2020)
Sensors (Basel, Switzerland)

مصطلحات موضوعية: Crowd management, Computer science, Automated counting systems, Real-time computing, Pedestrian movement dynamics, 02 engineering and technology, RNN-LSTM, lcsh:Chemical technology, Biochemistry, Article, Analytical Chemistry, Crowds, Crowd monitoring system, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, lcsh:TP1-1185, Electrical and Electronic Engineering, Wi-Fi sensor data, Instrumentation, TRACE (psycholinguistics), 050210 logistics & transportation, ARMAX, Event (computing), 05 social sciences, 020206 networking & telecommunications, Data fusion, Sensor fusion, Atomic and Molecular Physics, and Optics, Recurrent neural network, Mass events, Feature (computer vision), Data_GENERAL

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1e4224694dbae0f239d58186e6649bb
https://doi.org/10.3390/s20216032

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