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Fruits and Vegetables Detection for Visually Impaired Person

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dc.contributor.author Feroz, Muntasir
dc.contributor.author Nahian, Noor
dc.contributor.author Kona, Kamrun Nahar
dc.date.accessioned 2022-09-05T04:11:36Z
dc.date.available 2022-09-05T04:11:36Z
dc.date.issued 2019-08-05
dc.identifier.uri http://dspace.ewubd.edu:8080/handle/123456789/3697
dc.description This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh. en_US
dc.description.abstract Fruits and Vegetables Detection For Visually Impaired Person plays an important role in Application Systems. It helps the customers to identify their desired fruits and vegetables not only by image but also with identifying sound. The main purpose of this mobile application system is to help blind people to identify fruits and vegetables so that they can purchase their food on their own. It can be also used by robots and in the conveyor belt of factories. However, convolutional neural networks have proved to be potentially more effective. In this thesis, we present a convolutional neural network trained to classify and detect fruits and vegetables from multiple angles. en_US
dc.language.iso en_US en_US
dc.publisher East West University en_US
dc.relation.ispartofseries ;CSE00200
dc.subject Visually Impaired Person en_US
dc.title Fruits and Vegetables Detection for Visually Impaired Person en_US
dc.type Thesis en_US


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