목록Experiences & Study/Deep DAIV (7)
On the journey of
[논문읽기] U-Net: Convolutional Networks for Biomedical Image Segmentation
Original Paper ) https://arxiv.org/pdf/1505.04597.pdf (https://arxiv.org/abs/1505.04597) U-Net: Convolutional Networks for Biomedical Image Segmentation There is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and training strategy that relies on the strong use of data augmentation to use the available..
[논문읽기] Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence
Original Paper ) Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence - PubMed (nih.gov) or Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence | Epilepsy and Seizures | JAMA Neurology | JAMA Network Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence - PubMed In this study, SCORE-AI ach..
[논문읽기] Lung Disease Classification Using Deep Learning Models from Chest X-ray Images(2023)
Original Paper ) https://ieeexplore.ieee.org/document/10075968/ Lung Disease Classification Using Deep Learning Models from Chest X-ray Images In the very recent past, Infectious disease-related sickness has long posed a concern on a global scale. Each year, COVID-19, pneumonia, and tuberculosis cause a large number of deaths because they all affect the lungs. Early detection and diagnosis can i..