Machine Learning-based Strategies for Crop Assessment in Diverse Districts of Uttarakhand-Reference-Cited by-同舟云学术

Machine Learning-based Strategies for Crop Assessment in Diverse Districts of Uttarakhand

Published:2024-05-17 Issue: Volume:45 Page:1-6
ISSN:
Container-title:2024 Second International Conference on Data Science and Information System (ICDSIS)
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Author:

Pant Janmejay¹,Pant Pushpa²,Bhatt Jaishankar³,Singh Devendra¹,Mohan Lalit⁴,Pant Hitesh Kumar⁵

Affiliation:

1. Graphic Era Hill University,Department of Computer Science and Engineering,Bhimtal Campus,India

2. M.B. Govt. P.G College,Department of Geography,Haldwani,India

3. Graphic Era Deemed to be University,Department of Computer Science and Engineering,Dehradun,Uttarakhand,India

4. GL Bajaj Institute of Technology and management,Noida,India

5. Kumaun University,Department of Management Studies,Bhimtal,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10593798/10594006/10594284.pdf?arnumber=10594284

Reference24 articles.

1. A computer vision system for early stage grape yield estimation based on shoot detection

2. A hybrid ensemble for classification in multiclass datasets: An application to oilseed disease dataset

3. Monitoring soil water content for decision supporting in agricultural water management based on critical threshold values adopted for Andosol in the temperate monsoon climate

4. A comparison of machine learning algorithms for regional wheat yield prediction using NDVI time series of SPOT-VGT | Semantic Scholar;Stas;A comparison of machine learning algorithms for regional wheat yield prediction using NDVI time series of SPOT-VGT | Semantic Scholar,2020

5. Potential of ensemble tree methods for early-season prediction of winter wheat yield from short time series of remotely sensed normalized difference vegetation index andin situmeteorological data