Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Semantic Segmentation of Rice Field Bund on Unmanned Aerial Vehicle Image using UNet

Créateur:
IdaI MI M
Éditeur:
IEEE
Hôte:

Visit

doi.org

Tasks

computer visionimage classification

Licenses

https://doi.org/10.15223/policy-029https://doi.org/10.15223/policy-037

Similaires

The effects of planting date on maize growth and development using unmanned aerial vehicle dataUNMANNED AERIAL VEHICLE (UAV)-BASED COMPUTER VISION MODEL FOR REAL-TIME BIRDS DETECTION IN RICE FARMDetection of asphalt roads degradation using Deep Learning applied to Unmanned Aerial Vehicle imageryTiny-ML Possibilities for the implementation of Keyemaba: Pest Detection and Prevention using Unmanned Aerial Vehicle on Farmland.Unmanned Aerial Vehicle (UAV) for Monitoring Soil Erosion in MoroccoAerial images collected by an Unmanned Aerial Vehicle in Hermitage, Réunion - 2023-12-07

The effects of planting date on maize growth and development using unmanned aerial vehicle data

Early detection of plant stress is important, particularly in the face of unpredictable climates. Co

UNMANNED AERIAL VEHICLE (UAV)-BASED COMPUTER VISION MODEL FOR REAL-TIME BIRDS DETECTION IN RICE FARM

Rice farming in Nigeria suffers significant losses due to bird damage, necessitating advanced mitiga

Detection of asphalt roads degradation using Deep Learning applied to Unmanned Aerial Vehicle imagery

Detection of asphalt roads degradation using Deep Learning applied to Unmanned Aerial Vehicle imagery

Poster presented at the Deep Learning Indaba 2023 by Adama COULIBALY

Tiny-ML Possibilities for the implementation of Keyemaba: Pest Detection and Prevention using Unmanned Aerial Vehicle on Farmland.

Tiny-ML Possibilities for the implementation of Keyemaba: Pest Detection and Prevention using Unmanned Aerial Vehicle on Farmland.

Poster presented at the Deep Learning Indaba 2022 by Segun Adebayo

Unmanned Aerial Vehicle (UAV) for Monitoring Soil Erosion in Morocco

This article presents an environmental remote sensing application using a UAV that is specifically a

Aerial images collected by an Unmanned Aerial Vehicle in Hermitage, Réunion - 2023-12-07

This dataset was collected by an Unmanned Aerial Vehicle in Hermitage, Réunion - 2023-12-07.