Smoothed-LSTM: Advancing spatio-temporal NDVI prediction in semi-automated dataset for rice crop-Reference-Cited by-同舟云学术

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Smoothed-LSTM: Advancing spatio-temporal NDVI prediction in semi-automated dataset for rice crop

Published:2024-04-08 Issue: Volume:17 Page:1-4
ISSN:
Container-title:2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS)
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Author:

Dey Anamika¹,Sarkar Somrita¹,Kumar Debajyoti¹,Mondal Arijit²,Mitra Pabitra³

Affiliation:

1. Indian Institute of Technology Kharagpur,Centre for Computational and Data Sciences,Kharagpur,India

2. Indian Institute of Technology,Department of Computer Science and Engineering,Patna,Bihta,India

3. Indian Institute of Technology Kharagpur,Department of Computer Science and Engineering,Kharagpur,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10543250/10544374/10544683.pdf?arnumber=10544683

Reference23 articles.

1. Prediction and forecast of pre-monsoon and post-monsoon groundwater level: using deep learning and statistical modelling

2. Modelling vegetation health and stress using hypersepctral remote sensing data

3. The use of ARIMA models for reliability forecasting and analysis

4. Forecast of NDVI in coniferous areas using temporal ARIMA analysis and climatic data at a regional scale

5. Deep Learning for Time Series Forecasting: Tutorial and Literature Survey

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