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This research studies the entrepreneurial model of distance intelligent classrooms, uses machine learning technology as the basis, and combines intelligent image recognition technology to identify the status and expression of students in distance education classrooms. Moreover, this paper has carried out a more detailed study of face detection and expression recognition technology and tried to apply it to classroom teaching evaluation, which has shown certain feasibility in experiments. At the end of this article, the system was tested and analyzed with the collected data, which verified the feasibility and accuracy of the system.<\/jats:p>","DOI":"10.3233\/jifs-189213","type":"journal-article","created":{"date-parts":[[2020,9,8]],"date-time":"2020-09-08T11:04:38Z","timestamp":1599563078000},"page":"2133-2144","source":"Crossref","is-referenced-by-count":19,"title":["Application of wireless network and machine learning algorithm in entrepreneurship education of remote intelligent classroom"],"prefix":"10.1177","volume":"40","author":[{"given":"Heping","family":"Lu","sequence":"first","affiliation":[{"name":"Center for Modern Educational Technology of Nantong University, Nantong, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"2","key":"10.3233\/JIFS-189213_ref1","doi-asserted-by":"crossref","first-page":"77","DOI":"10.17718\/tojde.00843","article-title":"Causes of Low Student Enrolment At The Zimbabwe Open 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