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Bengali Ethnicity Recognition and Gender Classification Using CNN & Transfer Learning

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dc.contributor.author Jewel, Md.
dc.contributor.author Hossain, Md. Ismail
dc.contributor.author Tonni, Tamanna Haider
dc.date.accessioned 2022-01-12T05:25:38Z
dc.date.available 2022-01-12T05:25:38Z
dc.date.issued 2019-11
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6704
dc.description.abstract In this paper, we have demonstrated how to apply CNN (Convolutional Neural Network) structured model and transfer learning to identify the ethnicity of Bengali people and it's a systematic process of gender classification too. We also applied several models of transfer learning like VGG16, Mobilenet, Resnet50, etc. to find out which model is more convenient to get our desired accuracy. But problems arise because there are many Indian people who look like and get dressed up like Bengali since in India many Bengali dwell in when many of them speak Bangla as well! (people of Kolkata along with some other provinces). So, the Bengali people are not only found in Bangladesh but also elsewhere in the world. That's why our model is based on facial images along with the tradition of their costumes. We tried to build a sophisticated model using CNN and transfer learning for this purpose and we got some tremendous performances applying transfer learning. en_US
dc.language.iso en_US en_US
dc.publisher IEEE en_US
dc.subject Data Augmentation en_US
dc.subject Ethnicity Recognition en_US
dc.subject Gender Classification en_US
dc.subject Convolutional Neural Network en_US
dc.subject Transfer Learning en_US
dc.subject Fine-Tuning en_US
dc.subject Deep Learning en_US
dc.subject Bottleneck Features en_US
dc.title Bengali Ethnicity Recognition and Gender Classification Using CNN & Transfer Learning en_US
dc.type Article en_US


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