Abstract: Accurate prediction of crops' yield is essential to develop farm management and food security. This paper presents the use of a hybrid deep model of Recurrent Neural Networks (RNNs) with ...
The transformation is documented in the study A Review of Drones in Smart Agriculture: Issues, Models, Trends, and Challenges ...
A new study reveals that the difference between the S&P 500’s earnings yield and long-term TIPS yield can forecast market ...
Leibniz-Centre for Agricultural Landscape Research (ZALF) e.V. Email: stefan [dot] stiller [at] zalf [dot] de, stillsen [at] gmail [dot] com This repository contains the code for the study ...
Abstract: Accurate in-season crop yield prediction is critical for timely agricultural decision-making, food security, and climate-resilient farm management. This study presents a framework for ...
The Huang-Huai-Hai region is a major winter wheat production area in China. Achieving accurate yield estimation through high spatio-temporal resolution MODIS remote sensing combined with ...
A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant measurements and environmental data. By training models on seven years of ...
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