TS<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e2056" altimg="si1.svg"><mml:msup><mml:mrow /><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math>HGRNet: A paradigm of two stream best deep learning feature fusion assisted framework for human gait analysis using controlled environment in smart cities-Reference-Cited by-同舟云学术

TS2HGRNet: A paradigm of two stream best deep learning feature fusion assisted framework for human gait analysis using controlled environment in smart cities

Published:2023-10 Issue: Volume:147 Page:292-303
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Khan Muhammad Attique,Mehmood Asif,Kadry Seifedine,Almujally Nouf Abdullah,Alhaisoni Majed,Balili Jamel,Al Hejaili Abdullah,Alanazi Abed,Alsubai Shtwai,Alqatani Abdullah

Funder

Princess Nourah Bint Abdulrahman University

Deanship of Scientific Research, King Khalid University

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference79 articles.

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5. Prevalence of lumbar spinal stenosis in general and clinical populations: a systematic review and meta-analysis;Jensen;Eur. Spine J.,2020

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