[HTML][HTML] Identification of soybean planting gaps using machine learning

FLP de Souza, MA Dias, TD Setiyono… - Smart Agricultural …, 2025 - Elsevier
The identification of planting gaps is essential for optimizing crop management in precision
agriculture. Traditional methods, such as manual scouting, are limited in scale and …

Molecular survey of flea-borne pathogens in fleas associated with carnivores from Algeria and an Artificial Neural Network-based risk analysis of flea-borne diseases

NR Sidhoum, M Boucheikhchoukh, C Azzouzi… - Research in Veterinary …, 2024 - Elsevier
As ectoparasites and efficient vectors of pathogens fleas constitute a source of nuisance for
animals as well as a major issue for public health in Algeria. In this study, a molecular survey …

Advancements and Challenges in Geospatial Artificial Intelligence, Evaluating Support Vector Machines Models for Dengue Fever Prediction: A Structured Literature …

H Meileni, NL Husni - International Journal of Advanced …, 2024 - search.ebscohost.com
This review examines recent advancements and ongoing challenges in applying Support
Vector Machines within Geospatial Artificial Intelligence, specifically for dengue fever …

[PDF][PDF] Using machine learning to predict disease outbreaks and enhance public health surveillance

F Ekundayo - 2024 - researchgate.net
Disease outbreaks pose significant challenges to public health systems, often requiring
rapid response strategies to mitigate widespread health and economic impacts. Traditional …