Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The gap between the actual and virtual worlds is closing at an incredible rate. Interaction with computers is becoming increasingly common as more people utilize them to complete a variety of jobs ranging from online learning to shopping. In such circumstances, identifying a user's level of involvement with the system with which he or she is engaging can modify how the system responds to the user. This will result in more engagement with the system as well as improved human-computer connection. In today's vision applications, including advertising, healthcare, autonomous vehicles, and e-learning, identifying user engagement might be critical. An automated engagement detection system that can analyze a person’s engagement outcome with a certain object or an environment can be crucial to many organizations and businesses around the globe. Therefore, we employ cutting-edge algorithms in our project to recognize user engagement levels and divide them into two categories: positive and negative.
"Automated Engagement Recognition in E-Environments", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.1110 - 1114, June-2022, Available :http://www.ijrti.org/papers/IJRTI2206175.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator