Detection of different Crops Types using RapidEye Imagery over Fresno, California-Reference-Cited by-同舟云学术

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Detection of different Crops Types using RapidEye Imagery over Fresno, California

Published:2022-11-18 Issue: Volume: Page:
ISSN:
Container-title:2022 3rd International Conference on Computing, Analytics and Networks (ICAN)
language:
Short-container-title:

Author:

Madaan Sanjay¹,Kaur Sukhjeet²

Affiliation:

1. Punjabi University,Computer Science and Engineering (UCOE),Patiala,India

2. Punjabi University,Department of Computer Science,Patiala,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10007061/10006842/10007181.pdf?arnumber=10007181

Reference20 articles.

1. Understanding deep learning in land use classification based on Sentinel?2 time series;campos?taberner;Sci Rep,2020

2. Use of time-series L-band UAVSAR data for the classification of agricultural fields in the San Joaquin Valley

3. Crop Type Mapping Based on Sentinel-1 Backscatter Time Series

4. Crop Classification using Multi-spectral and Multitemporal Satellite Imagery with Machine Learning

5. Comparison of CNN models for application in crop health assessment with participatory sensing

Cited by 1 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. Remote Sensing Applications in Almond Orchards: A Comprehensive Systematic Review of Current Insights, Research Gaps, and Future Prospects;Applied Sciences;2024-02-21

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