Cropformer: A new generalized deep learning classification approach for multi-scenario crop classification.

ABSTRACT: Accurate and efficient crop classification using remotely sensed data can provide fundamental and important information for crop yield estimation. Existing crop classification approaches are usually designed to be strong in some specific scenarios but not for multi-scenario crop classification. In this study, we proposed a new deep learning approach for multi-scenario crop classification, named Cropformer. Cropformer can extract global features and local features, to solve the problem that current crop classification methods extract a single feature. Specifically, Cropformer is a two-step classification approach, where the first step is self-supervised pre-training to accumulate knowledge of crop growth, and the second step is a fine-tuned supervised classification based on the weights fro

SUBMITTER: Wang H 

PROVIDER: S-EPMC10017990 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature