MVP—A Multistep Visual Pretraining Pipeline for Efficient Weather Recognition
TL;DR
MVP is a multistep visual pretraining pipeline designed to improve weather recognition from images, addressing challenges like overlapping visual features and high dataset costs. It has applications in traffic control, autonomous vehicles, and agriculture.
MVP—A Multistep Visual Pretraining Pipeline for Efficient Weather Recognition
Diego Acuña-Escobar; Monserrate Intriago-Pazmiño; Julio Ibarra-Fiallo
https://doi.org/10.1109/ACCESS.2025.3648029
Volume 14
Automatic weather recognition using images has important applications in land and air traffic control, autonomous vehicles, road safety, and crop management. Despite its relevance, this field remains underexplored due to the difficulty of extracting robust features for weather conditions that often overlap visually, and the high cost of building large, labeled datasets. To address these challenges...