{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:09:08Z","timestamp":1753884548765,"version":"3.41.2"},"reference-count":28,"publisher":"World Scientific Pub Co Pte Ltd","issue":"Supp01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Inter. Net."],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:p> In human-computer interaction and virtual truth, hand pose estimation is essential. Public dataset experimental analysis Different biometric shows that a particular system creates low manual estimation errors and has a more significant opportunity for new hand pose estimation activity. Due to the fluctuations, self-occlusion, and specific modulations, the structure of hand photographs is quite tricky. Hence, this paper proposes a Hybrid approach based on machine learning (HABoML) to enhance the current competitiveness, performance experience, experimental hand shape, and key point estimation analysis. In terms of strengthening the ability to make better self-occlusion adjustments and special handshake and poses estimations, the machine learning algorithm is combined with a hybrid approach. The experiment results helped define a set of follow-up experiments for the proposed systems in this field, which had a high efficiency and performance level. The HABoML strategy decreased analysis precision by 9.33% and is a better solution. <\/jats:p>","DOI":"10.1142\/s0219265921410218","type":"journal-article","created":{"date-parts":[[2022,1,8]],"date-time":"2022-01-08T03:13:04Z","timestamp":1641611584000},"source":"Crossref","is-referenced-by-count":0,"title":["Hybrid Approach Based on Machine Learning for Hand Shape and Key Point\u2019s Estimation"],"prefix":"10.1142","volume":"22","author":[{"given":"Zhongshan","family":"Chen","sequence":"first","affiliation":[{"name":"School of Mathematics and Information Science, Nanjing Normal University of Special Education, 1 Shennong Road, Qixia District, Nanjing, P. R. China"}]},{"given":"Xinning","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Communication Engineering, Tongda College of Nanjing University of Posts & Telecommunications, 33 Runyang South Road, Hanjiang District, Yangzhou, P. R. China"}]},{"given":"Oscar Sanju\u00e1n","family":"Mart\u00ednez","sequence":"additional","affiliation":[{"name":"Universidad Internacional de La Rioja, Spain"}]},{"given":"Rub\u00e9n Gonz\u00e1lez","family":"Crespo","sequence":"additional","affiliation":[{"name":"School of Engineering and Technology, Universidad Internacional de La Rioja, 26006, Spain"}]}],"member":"219","published-online":{"date-parts":[[2022,1,7]]},"reference":[{"key":"S0219265921410218BIB001","doi-asserted-by":"publisher","DOI":"10.3390\/en11061561"},{"key":"S0219265921410218BIB002","doi-asserted-by":"publisher","DOI":"10.3847\/1538-4357\/aaa23c"},{"key":"S0219265921410218BIB003","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.11.011"},{"key":"S0219265921410218BIB004","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2020.01.140"},{"key":"S0219265921410218BIB005","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04249-y"},{"key":"S0219265921410218BIB006","doi-asserted-by":"publisher","DOI":"10.1002\/ett.3789"},{"key":"S0219265921410218BIB007","doi-asserted-by":"publisher","DOI":"10.3390\/electronics8111210"},{"key":"S0219265921410218BIB008","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-017-5044-z"},{"key":"S0219265921410218BIB009","doi-asserted-by":"publisher","DOI":"10.1007\/s10617-018-9203-6"},{"issue":"1","key":"S0219265921410218BIB011","volume":"26","author":"Mezhoud N.","year":"2011","journal-title":"Journal of Theoritical and Applied Information Technology"},{"key":"S0219265921410218BIB012","first-page":"1","author":"Ahmad F. 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