Classification of Fruits using Convolutional Neural Networks
Author:
Affiliation:
1. PCCOE,Department of Information Technolgy,Pune,India
2. PCCOE,Department of Computer Engineering,Pune,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9807685/9807649/09808070.pdf?arnumber=9808070
Reference12 articles.
1. Particle Swarm Optimized Fuzzy Model for the Classification of Banana Ripeness
2. Fruit recognition from images using deep learning
3. Shape-based Fruit Recognition and Classification
4. Classification of Fruits Using Computer Vision and a Multiclass Support Vector Machine
5. Efficient Knowledge Transformation for Incremental Learning and Detection of New Concept Class in Students Classification System
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1. Classification of Red Watermelon Varieties Using Canny Edge Detection and CNN;2024 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS);2024-06-29
2. Tomato (Solanum lycopersicum L.) Fruit Ripeness Classification based on VGG16 Convolutional Neural Network;2024 The 8th International Conference on Machine Learning and Soft Computing;2024-01-26
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