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Real Time Classification and Localization of Herb’s Leaves Using Yolo

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dc.contributor.author Shoreef Uddin, Md.
dc.contributor.author Abdullah
dc.date.accessioned 2020-12-07T11:11:31Z
dc.date.available 2020-12-07T11:11:31Z
dc.date.issued 2020-07
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/5338
dc.description.abstract Day by day the usage of Artificial Intelligence makes our life easier and comfortable. Machines are started to learn as like human. Complex Problems can be solved easily by Artificial Intelligence. A machine can only do computing. By using the computing technique a machine can detect or classify objects. Getting higher accuracy and reducing prediction times are always the biggest challenges for image classification. Herbs have played a major parts in medical science for thousands year. Herbs have the ability to combat with diseases. People have less amount of knowledge about herbs as a result it becomes an issue to recognize them. Using poisonous plant as medication might increase the risk of life in serious way. In this paper we will discuss about how to classify and localize five types of herbs. Those five types of herbs are Mehdi, Betel, Mint, Basil and Aloe Vera. We will build a Neural Network model and train the model to classify the herbs. In Future we can implement the trained model into a mobile application which will help user to learn about herbal remedies. Therefore, we are proposing a novel approach for classifying herbs and also localizing the individual herb by using artificial intelligence. en_US
dc.language.iso en en_US
dc.publisher Daffodil International University en_US
dc.subject Classification en_US
dc.subject Software Localization en_US
dc.title Real Time Classification and Localization of Herb’s Leaves Using Yolo en_US
dc.type Other en_US

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