Dataset for Detection of non-invasive sexing of early chick embryos in intact eggs using laser speckle contrast imaging and deep neural networks

Dataset for article: Detection of non-invasive sexing of early chick embryos in intact eggs using laser speckle contrast imaging and deep neural networks by Simon Mahler, Anika Arora, Carol Readhead, Siyuan Yin, Surya Narayanan Hari, Ellie Wang, Cecilia I. Moxley, Abdullahi A. Adeboye, Zhenyu Dong, Haowen Zhou, Xi Chen, Marianne Bronner, and Changhuei Yang Dataset of LSCI chick embryo blood vessel images. This dataset enables reproduction of the results presented in the publication using machine learning (ML) or deep neural network (DNN) approaches. The data are organized into two classes: HH19 and HH25. Please read the readme.txt document before using the dataset.本数据集配套论文：《采用激光散斑衬比成像与深度神经网络实现完整鸡蛋内鸡胚早期无创性别鉴定》，作者为Simon Mahler、Anika Arora、Carol Readhead、Siyuan Yin、Surya Narayanan Hari、Ellie Wang、Cecilia I. Moxley、Abdullahi A. Adeboye、Zhenyu Dong、Haowen Zhou、Xi Chen、Marianne Bronner及Changhuei Yang。本数据集包含激光散斑衬比成像（LSCI）获取的鸡胚血管图像，可复现该论文中采用机器学习（ML）或深度神经网络（DNN）方法得到的研究结果。数据分为HH19与HH25两个类别，请在使用本数据集前仔细阅读readme.txt文档。