Empirical Study of Crop-disease Detection and Crop-yield Analysis Systems: A Statistical View
Author:
Affiliation:
1. LPU,Department of Electronics and Tele-Communication Engineering,Punjab,India
2. LPU,Department of Computer Science and Engineering,Punjab,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9758147/9758153/09758284.pdf?arnumber=9758284
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1. Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea
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3. Fully Convolutional Siamese Autoencoder for Change Detection in UAV Aerial Images
4. Rain-Type Classification From Microwave Satellite Observations Using Deep Neural Network Segmentation
5. Cropland Mapping and Change Detection: Toward Zimbabwean Cropland Inventory
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Advancements in Agricultural Technology: A Comprehensive Review of Machine Learning and Deep Learning Approaches for Crop Management and Disease Detection;International Journal of Advanced Research in Science, Communication and Technology;2024-02-11
2. Crop Disease Detection and Classification Using Deep Learning-Based Classifier Algorithm;Emerging Trends in Expert Applications and Security;2023
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