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Exploring the efficiency of transfer learning in Brinjal disease detection using deep learning

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dc.contributor.author Hasan, MD. Zahid
dc.date.accessioned 2025-08-30T04:50:40Z
dc.date.available 2025-08-30T04:50:40Z
dc.date.issued 2024-09-01
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14114
dc.description Thesis en_US
dc.description.abstract About 75% of the people in Asian countries rely on agriculture for their livelihood. Bangladesh is a country highly dependent on agriculture [1]. About 45.33% of the population of the country was engaged in the agriculture sector in the fiscal year 2022–2023 [2]. And same sector contributed approximately 11.38% to the Gross Domestic Product of the nation [3]. Grown over 50,000 hectares of land, eggplant, or brinjal, is the third most important crop in the nation [4]. This vegetable is very beneficial to health as it aids in better digestion and increases mental performance. It is also known to prevent one from catching cancer, protects heart health, and also supports the bones in one's body. Antioxidants, including vitamins A and C, which protect cells from damage, are very much present in brinjal. It has a high concentration of polyphenols, which are chemical molecules that help control how sugar is metabolized in diabetic cells en_US
dc.description.sponsorship DIU en_US
dc.publisher DAFFODIL INTERNATIONAL UNIVERSITY en_US
dc.subject Transfer Learning en_US
dc.subject Deep Learning en_US
dc.subject Brinjal Disease Detection en_US
dc.subject Convolutional Neural Networks (CNNs) en_US
dc.subject Plant Pathology en_US
dc.title Exploring the efficiency of transfer learning in Brinjal disease detection using deep learning en_US
dc.type Thesis en_US


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