The HAWKwood Database
Christopher Herbon

TL;DR
The HAWKwood Database provides a comprehensive collection of real and synthetic wood pile images, serving as a benchmark for evaluating detection and surveying algorithms across various categories.
Contribution
This paper introduces a diverse, categorized database of wood pile images with ground truth and measurements for benchmarking algorithm performance.
Findings
Provides 7655 images across six categories
Includes ground truth data and forestry measurements
Facilitates standardized evaluation of wood detection algorithms
Abstract
We present a database consisting of wood pile images, which can be used as a benchmark to evaluate the performance of wood pile detection and surveying algorithms. We distinguish six database cate- gories which can be used for different types of algorithms. Images of real and synthetic scenes are provided, which consist of 7655 images divided into 354 data sets. Depending on the category the data sets either include ground truth data or forestry specific measurements with which algorithms may be compared.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRemote Sensing and LiDAR Applications · Wood and Agarwood Research · Automated Road and Building Extraction
