Blonder Benjamin, Both Sabine, Jodra Miguel, Majalap Noreen, Burslem David, Teh Yit Arn, Malhi Yadvinder
Environmental Change Institute, School of Geography and the Environment, University of Oxford, South Parks Road, Oxford, OX1 3QY, UK.
School of Biological Sciences, University of Aberdeen, Zoology Building, Tillydrone Avenue, Aberdeen, AB24 2TZ, UK.
Ecology. 2019 Nov;100(11):e02844. doi: 10.1002/ecy.2844. Epub 2019 Aug 16.
The data set contains images of leaf venation networks obtained from tree species in Malaysian Borneo. The data set contains 726 leaves from 295 species comprising 50 families, sampled from eight forest plots in Sabah. Image extents are approximately 1 × 1 cm, or 50 megapixels. All images contain a region of interest in which all veins have been hand traced. The complete data set includes over 30 billion pixels, of which more than 600 million have been validated by hand tracing. These images are suitable for morphological characterization of these species, as well as for training of machine-learning algorithms that segment biological networks from images. Data are made available under the Open Data Commons Attribution License. You are free to copy, distribute, and use the database; to produce works from the database; and to modify, transform, and build upon the database. You must attribute any public use of the database, or works produced from the database, in the manner specified in the license. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the database and keep intact any notices on the original database.
该数据集包含从马来西亚婆罗洲的树种获取的叶脉网络图像。该数据集包含来自50个科295个物种的726片叶子，这些叶子采自沙巴的8个森林样地。图像范围约为1×1厘米，或500万像素。所有图像都包含一个感兴趣区域，其中所有叶脉都已手动描绘。完整的数据集包括超过300亿像素，其中超过6亿像素已通过手动描绘进行了验证。这些图像适用于这些物种的形态特征描述，以及用于从图像中分割生物网络的机器学习算法的训练。数据依据开放数据共享署名许可协议提供。你可以自由复制、分发和使用该数据库；从数据库中创作作品；以及修改、转换和基于该数据库进行构建。你必须按照许可协议中规定的方式对数据库的任何公共使用或从数据库中创作的作品进行署名。对于数据库的任何使用或重新分发，或从中创作的作品，你必须向他人明确说明数据库的许可协议，并保留原始数据库上的所有通知。
