Detection and Identification of Rice Pests Using Memory Efficient Convolutional Neural Network
Author:
Affiliation:
1. Green University of Bangladesh,Department of Computer Science and Engineering,Bangladesh
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10084914/10084930/10084936.pdf?arnumber=10084936
Reference13 articles.
1. Dataset;annafii,0
2. Paddy Doctor: A Visual Image Dataset for Paddy Disease Classification;murugan,0
3. Rice Leafs;riyaz;Kaggle,2019
4. IP102-Dataset;mahjabin;Kaggle,2022
5. A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework
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2. Research on Rice Pest Detection Method Based on Feature Fusion;2023 7th Asian Conference on Artificial Intelligence Technology (ACAIT);2023-11-10
3. An In-Depth Analysis of Deep Learning and Machine Learning Methods for Identifying Rice Leaf Diseases;2023 4th International Conference on Smart Electronics and Communication (ICOSEC);2023-09-20
4. RiPa-Net: Recognition of Rice Paddy Diseases with Duo-Layers of CNNs Fostered by Feature Transformation and Selection;Biomimetics;2023-09-07
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