danaroth/whu_hi
The WHU‑Hi dataset (Wuhan UAV‑borne Hyperspectral Images) was collected and shared by the RSIDEA research group at Wuhan University, serving as a benchmark for precise crop classification and hyperspectral image classification research. It comprises three independent UAV‑borne hyperspectral datasets: WHU‑Hi‑LongKou, WHU‑Hi‑HanChuan, and WHU‑Hi‑HongHu, all captured over agricultural areas in Hubei Province, China. The data were acquired using a Headwall Nano‑Hyperspec sensor mounted on UAV platforms, providing high spatial resolution (H2 images). Pre‑processing includes radiometric calibration and geometric correction performed with the HyperSpec software supplied by the instrument vendor. Each dataset includes detailed acquisition metadata (time, weather, sensor, flight altitude, image size, number of bands, spatial resolution) and sample counts for various crop classes.
Description
Dataset Overview
Title
Revisiting the Performance of Deep Learning‑Based Vulnerability Detection on Realistic Datasets
Description
This repository contains the dataset and scripts for studying the performance of deep‑learning‑based vulnerability detection on realistic datasets.
Relevant Information
- DOI: 10.1109/TSE.2024.3423712
- Abstract link: https://zenodo.org/records/12707476
- Release date: July 5 2024
- Version: 0.1
Files
- Replication package: Replication Package.zip
- Appendix PDF: Revisiting_the_Performance_of_Deep_Learning_Based_Vulnerability_Detection_on_Realistic_Datasets__Appendix.pdf
- README: Readme.md
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Topics
Source
Organization: Wuhan University RSIDEA
Created: Unknown
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