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Browsing Project Report by Subject "MobileNetV2"

Browsing Project Report by Subject "MobileNetV2"

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  • Comparative Analysis of Transfer Learning Models and Custom CNN for Tea Leaf Disease Classification 
    Pappu, Prosenjith Dash; Akter, Mst. Aklima (Daffodil International University, 2025-09-17)
    Tea is one of the most consumed drinks in the world and a savior of agricultural economies especially to nations like Bangladesh, India and Sri Lanka. However, diseases of the leaves like Algal Leaf, Gray Blight, Helopeltis, ...
  • Decentralized Deep Learning for Rose Leaf Disease Detection: A Federated CNN Approach 
    Sowa, Pithila Mostofa; Islam, Syful (Daffodil International University, 2025-09-17)
    Rose is considered useful in agriculture and horticulture. Their leaves are however highly prone to illness such like black spot, mildew and mosaic virus. Such diseases may reduce the yield as well as quality. The conventional ...
  • Deep Learning Approaches For Analyzing Microscopic Peripheral Blood Cell Images. 
    Rahik, Rafikul Ahsan; Kulsum, Umme (Daffodil International University, 2025-01-12)
    The diagnosis of numerous hematological disorders depends on the precise and effective classification of peripheral blood cells. However, in high-throughput or resource-constrained contexts, the manual evaluation of ...
  • Fruit Quality Classification using Deep Learning and Explainable AI 
    Annafi, Abdun Nafi; Muhtasim, Tasnuva (Daffodil International University, 2025-05-14)
    Fruit quality classification is a critical task in agriculture and food industries to ensure standardization and market value. This study evaluates the performance of VGG19, MobileNetV2, ResNet50, custom CNN and BiLSTM for ...
  • A proposed deep learning approach for Bangla handwritten character recognition 
    Mahmud, Shadhin (Daffodil International University, 2024-01-24)
    The present research on Bangla Handwritten Character Identification investigated a wide range of deep learning architectures, including DenseNet201, VGG19, MobileNetV2, ResNet101, CNN01, and CNN02, and evaluated their ...
  • Smart Garbage Classification System Using Ml Algorithm 
    Pranto, Yousuf Talukder (Daffodil International University, 2025-05-14)
    Growing landfill volumes and slow, labour-intensive sorting have made urban waste one of today’s least glamorous bottlenecks. To tackle that gap, this study builds an image-based classification pipeline that recognises ...

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