遇见数据集

Example Dataset for Hydrographic Segmentation with Meta-Learning (Single HUC Code)

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NIAID Data Ecosystem2026-05-02 收录
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This dataset provides a representative sample used in the study "Hydrographic Segmentation with Meta-Learning". It includes preprocessed input features and corresponding label masks for a single HUC (190901031707) watershed. The data is formatted as NumPy arrays and is intended to support reproducibility and demonstration of the methods implemented in the associated GitHub repository: https://github.com/N-Jaro/hydrographic-segmentation-meta-learning. The dataset can be used to test and understand the input-output structure, preprocessing format, and model workflow of the hydrographic segmentation pipeline. It is not intended for training or benchmarking at scale. Contents: Input data (.npy) containing multiple feature channels (e.g., DEM, slope, aspect, etc.)Segmentation label (.npy) representing the hydrographic featuresFile Format: NumPy arrays (.npy) Size: ~48 MB total License: CC BY 4.0 Author: Nattapon Jaroenchai (nj7@illinois.edu) Date Published: 7/17/2025 Note: The full dataset used in the study is sourced from the U.S. Geological Survey (USGS) and is subject to institutional data access policies. This sample is shared for demonstration and educational purposes.

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2025-07-17
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