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GI-SleepNet: A Highly Versatile Image-based Sleep Classification using a Deep Learning Algorithm
Sleep-stage classification is essential for sleep research. Various automatic judgment programs including deep learning algorithms using artificial intelligence (AI) have been developed, but with limitations in data format compatibility, human interpretability, cost, and technical requirements. We developed a novel program called GI-SleepNet, generative adversarial network (GAN)-assisted image-based sleep staging for mice that is accurate, versatile, compact, and easy to use. In this program,doi:10.21203/rs.3.rs-586116/v1 fatcat:daqarl5kprcjhhlfq4pswqt4pe