{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T11:07:40Z","timestamp":1781089660142,"version":"3.54.1"},"reference-count":31,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,5,24]],"date-time":"2026-05-24T00:00:00Z","timestamp":1779580800000},"content-version":"vor","delay-in-days":23,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Computer Animation &amp;amp; Virtual"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Hand gesture recognition portrays a vital role in prompting a realistic interaction between humans and computers. It has potential around diverse domains, such as assistive technologies, virtual reality and healthcare. Even though conventional static gesture recognition has attained significant advancements, dynamic gestures are more challenging to recognize because they rely on occlusions, spatiotemporal cues and environmental changes. While current deep learning and transformer\u2010based models enhanced accuracy, there remain some issues related to interpretability, computational efficiency and robustness. This research presents a Gabor\u2010augmented with Temporal Attention and User\u2010interface Framework (GTAU\u2010F), implemented for recognizing semantic dynamic hand gestures. GTAU\u2010F emphasizes a Gabor\u2010enhanced inflated 3D two\u2010stream network for extracting spatio\u2010temporal features, together with an attention\u2010guided GoogLeNet that integrates temporal encoding and builder optimization for coherent convergence. To facilitate certain interpretation, Gradient\u2010weighted Class Activation Mapping++ (Grad\u2010CAM++) visualizations are employed, and a human\u2010centric adaptive gesture interface facilitates real\u2010time, user\u2010friendly interactions. Assessment outcomes based on four datasets (ChaLearn LAP IsoGD, NvGesture, EgoGesture, and Hand gesture recognition database) illustrate that GTAU\u2010F attains over 99% in accuracy, precision, recall, and specificity. Finally, GTAU\u2010F emerges as an efficient, robust and interpretable solution for enhancing dynamic gesture recognition in human\u2013computer interactions.<\/jats:p>","DOI":"10.1002\/cav.70118","type":"journal-article","created":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T02:12:07Z","timestamp":1779675127000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Gabor\u2010Augmented Two\u2010Stream Framework With\n                    <scp>GoogLeNet<\/scp>\n                    \u2010Based Temporal Attention for Semantic Dynamic Hand Gesture Recognition"],"prefix":"10.1002","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5928-1273","authenticated-orcid":false,"given":"A. D.","family":"Harale","sequence":"first","affiliation":[{"name":"Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering Korti  Solapur Maharashtra India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kailash Jagannath","family":"Karande","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering Korti  Solapur Maharashtra India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,5,24]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3456436"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-023-01173-6"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10209-024-01139-6"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3421992"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/app14031012"},{"key":"e_1_2_11_7_1","article-title":"Hand Gesture Recognition Systems: A Review of Methods, Datasets, and Emerging Trends","volume":"975","author":"Sarowar M.","year":"2025","journal-title":"International Journal of Computer 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