Former Nickelodeon child star Kianna Underwood has been identified as the victim in a terrible hit-and-run collision that left her dead after she was dragged down two Brooklyn blocks early Friday ...
By combining machine learning, robotics and analytics, farmers are gaining financial benefits by improving crop yields and ...
Industrial AI deployment traditionally requires onsite ML specialists and custom models per location. Five strategies ...
AI-driven platforms increasingly assist farmers in choosing when to plant, irrigate, fertilize, or harvest. These systems ...
The transformation is documented in the study A Review of Drones in Smart Agriculture: Issues, Models, Trends, and Challenges ...
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AI breeding aims to boost orphan crops and strengthen food security
Artificial intelligence is quietly reshaping how crops are bred, and the biggest gains may come not in corn or wheat but in the neglected staples that feed millions on the margins. By pairing ...
Accurately predicting complex agronomic traits remains a major bottleneck in crop breeding. This study demonstrates how optimized genomic prediction models can reliably forecast flowering time, yield ...
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 ...
Introduction: The yield of ginkgo biloba leaves serves as a critical indicator for assessing their growth and health status. However, current assessment methods primarily rely on manual harvesting and ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India Center for Machine Intelligence and Data Science, Indian Institute of Technology Bombay, Powai, Mumbai ...
Introduction: Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods ...
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