| Summary: | 碩士 === 國立臺灣科技大學 === 企業管理系 === 107 === The research starts from the perspective of the selection of enterprises’ talents. While focusing on the process of traditional recruitment, current implementations have always failed to solve the problem of talents recruitment.
In order to understand the limitations of current academics, it’s worthy to explore the advantages and disadvantages of this domain. Through the techniques of facial recognition and machine learning combined with facial features in Physiognomy, we develop a platform called “Instant Personality Analysis of Facial Features”. Through integrating Artificial Intelligence, big data with facial and competency definitions, this platform provides us the information of potential personality analysis, expected to improve recruitment more efficiency, reduce potential risks and make up a deficiency of other selection tools.
This study adopts the methods of general natural science experimentations, and literature review, for analyzing the correlation between Physiognomy and talent selection. The research utilizes open source technology, facial features detection and Cloud System’s instant facial image classification technology to dynamically and immediately capture images, then uploading to the cloud artificial intelligence service of analysis. The facial features will be compared to Physiognomy database thus obtain the facial analysis of the subject. The recommendations obtained from the correlation results of Physiognomy and selection analysis can provide a basis for the company to consider more when selecting talents
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