Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Artificial intelligence and deep learning based technologies for emerging disease recognition and pest prediction in beans (phaseolus vulgaris l.): A systematic review

Domain:

agriculture

Record type:

paper
Creator:
PenMkwA. Rap
Publisher:
Aca
Host:

Visit

doi.org

Similar

Digital technologies in rice blast disease management: a comprehensive systematic review of artificial intelligence, IoT, blockchain, and emerging digital toolsPhysical and Mechanical Properties of Selected Common Beans (Phaseolus vulgaris L.) Cultivated in TanzaniaAdvancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AIGenetic Diversity of African Common Bean (Phaseolus vulgaris L.) Germplasm: A Systematic Review of Molecular Studies and Breeding ImplicationsComparison of Deep Learning Technologies Applied to the Recognition of Defects in Cocoa BeansArabic Speech Recognition and Artificial Intelligence Technologies

Digital technologies in rice blast disease management: a comprehensive systematic review of artificial intelligence, IoT, blockchain, and emerging digital tools

Physical and Mechanical Properties of Selected Common Beans (Phaseolus vulgaris L.) Cultivated in Tanzania

The physical and mechanical properties of foods are important, if not essential, in the design of su

Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI

Abstract Common beans (CB), a vital source for high protein content, plays a crucial role in ensuri

Genetic Diversity of African Common Bean (Phaseolus vulgaris L.) Germplasm: A Systematic Review of Molecular Studies and Breeding Implications

This systematic review aims to consolidate current knowledge on the genetic diversity of African com

Comparison of Deep Learning Technologies Applied to the Recognition of Defects in Cocoa Beans

Arabic Speech Recognition and Artificial Intelligence Technologies

This article presents a compilation on the use and impacts of artificial intelligence technologies i