Crop yield predictive modeling using optimized deep convolutional neural network: An automated crop management system

In agriculture, AI devices have developed tools that help farmers in achieving exact and controlled cultivation. Besides, it helps farmers with suitable assistance in auspicious harvesting, frequent change of crops, water management, kind of crops to be grown-up, optimum plantation, pest attack, and...

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Veröffentlicht in:	Multimedia tools and applications 2024-04, Vol.83 (14), p.40295-40322
Hauptverfasser:	Jorvekar, Priti Prakash, Wagh, Sharmila Kishor, Prasad, Jayashree Rajesh
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive algorithms Agricultural production Air temperature Artificial neural networks Bulk density Computer Communication Networks Computer Science Crop yield Data Structures and Information Theory Deep learning Dew point Feature extraction Harvesting Machine learning Mathematical models Morning Multimedia Information Systems Neural networks Parameters Prediction models Soil moisture Soil porosity Soil temperature Special Purpose and Application-Based Systems Water management Wind speed
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