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A Study on Predicting Body Weight through Footprints Using Fuzzy Logic

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dc.contributor.author Adnan, Sahid
dc.contributor.author Sarkar, Mitu
dc.contributor.author Ramim, Shadakat Hossain
dc.date.accessioned 2022-02-09T04:33:46Z
dc.date.available 2022-02-09T04:33:46Z
dc.date.issued 2021-06-02
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7029
dc.description.abstract Predicting body weight by scanning only footprints is an emerging topic of research. There are lots of statistics in different regions of the earth. There are several techniques to detect body weight from footprints. This study reviews some recent phenomena. But the inputs or scanning of images are vague in major cases. Crisp measurements deliver results with an error. Fuzzy logic captures the uncertain systems perfectly. In this study, a fuzzy logic model has been designed for predicting body weights from footprints. Here length, area of feet and gender are taken inputs for the Mamdani FIS system. These inputs are perfect for detecting body weights. This study also compares similar results. This study also includes discussing human body weight prediction from footprints by deep learning method and statistical analysis for male females’ body weight through their footprints. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Footprints en_US
dc.subject Body weight en_US
dc.subject Fuzzy logic en_US
dc.subject Statistical analysis en_US
dc.subject Deep learning en_US
dc.title A Study on Predicting Body Weight through Footprints Using Fuzzy Logic en_US
dc.type Article en_US

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