Terms in plain language
- Prototype (three training-feature cluster centres per crop class): K-means centres learned from balanced training-pixel embeddings of the first temporal block. Standardized, normalized embeddings are compared with the centres; temperature-scaled similarities and log-sum-exp form class scores, then softmax gives probabilities. It adds no labeled patches and shares the SAM encoder.
- SAM optimizer (sharpness-aware minimization): an optimization method; this project does not use Segment Anything foundation features.
- New CNN control (a separately trained plain per-pixel temporal CNN): the same 28,306-parameter architecture as the old temporal CNN, trained under the newer matched-control RNG protocol. A control for attention/Transformer experiments, not a new large backbone.
- Blend (probability-weighted prediction ensemble): combine class probabilities, then take argmax. No checkpoint-weight averaging or majority vote.
- Highest observed test configuration: attention-CNN addition at seed3407, 49.5298% test. It is kept separately because its validation is below the recommendation.
- Validation-selected recommendation: new plain-CNN addition at seed3407, 52.5640% validation and 49.4555% test.