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Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach.

, , , , , and . CoRR, (2021)

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Detecting In-Season Crop Nitrogen Stress of Corn for Field Trials Using UAV- and CubeSat-Based Multispectral Sensing., , , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 12 (12): 5153-5166 (2019)Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach., , , , , and . CoRR, (2021)Correction: Lin et al. Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens. 2021, 13, 1740., , , , , , and . Remote. Sens., 15 (1): 141 (January 2023)Predicting the growth trajectory and yield of greenhouse strawberries based on knowledge-guided computer vision., , , , and . Comput. Electron. Agric., (2024)Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa., , , , and . Remote Sensing, 9 (9): 931 (2017)Physics Guided Neural Networks for Time-Aware Fairness: An Application in Crop Yield Prediction., , , , , and . AAAI, page 14223-14231. AAAI Press, (2023)Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping., , , , and . CoRR, (2021)Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification From VHR Imagery., , , , and . IEEE Trans. Geosci. Remote. Sens., 59 (1): 139-150 (2021)FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems., , , , , , , , and . CoRR, (2023)Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability., , , , and . AAAI, page 14365-14373. AAAI Press, (2023)