# Semantic Segmentation on Global Wheat Full (dev) Source: [Semantic Segmentation on Global Wheat Full (dev)]() Collection index: [llms.txt]() Data updated: 2026-02-26T06:10:44.901Z Evaluation of Semantic Segmentation performance on the development split of the Global Wheat Full dataset, reporting mIoU. A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Semantic Segmentation | | Dataset (including any stated split) | Global Wheat Full (dev) | | Metric | mIoU | | Unit | SCALAR | | Direction | Higher is better | | Results loaded | 1 of 1 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [mIoU](): Higher is better; unit: SCALAR. ## Recorded results | Method | mIoU | Result date | Report paper | | --- | --- | --- | --- | | Proposed Self-Training Framework | 0.748 | Not recorded | 6940e791456146936284f74d | ### Proposed Self-Training Framework mIoU: 0.748. Result ID: 699881685698665ec4e2a15c. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Backbone":"SegFormer","Training Strategy":"Two-Stage Hybrid (Iterative Teacher-Student Loop)","Cross-validation":"10-fold","Model Ensembling":"true","Test-Time Augmentation (TTA)":"true"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.