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.