通信系统综合设计，使用Pyqt进行了x光和CT的识别与分割，将OpenCV competition 的作品修改为了纯python

# Covid-19-Detection using Metrics based Few-Shot Learning This repository is implementation of Covid-Classification models using deep learning approaches. [Paper Link] (https://doi.org/10.1117/12.2581496) We have used following approaches for our experiments. 1. Logistic Regression (Baseline) 2. Convolutional Neural Networks. 3. Transfer Learning. 4. Siamese Networks (Few-Shot Learning) 5. Unsupervised learning (TSNE+PCA) ## Datset: 1. https://www.kaggle.com/tawsifurrahman/covid19-radiography-database 2. https://www.kaggle.com/pranavraikokte/covid19-image-dataset ## If you found our work useful, please consider citing us. Link: https://doi.org/10.1117/12.2581496 ``` @inproceedings{10.1117/12.2581496, author = {Shruti Jadon}, title = {{COVID-19 detection from scarce chest x-ray image data using few-shot deep learning approach}}, volume = {11601}, booktitle = {Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and Applications}, editor = {Thomas M. Deserno and Brian J. Park}, organization = {International Society for Optics and Photonics}, publisher = {SPIE}, pages = {161 -- 170}, keywords = {Deep Learning, Classification, Few-shot Learning, Less data, COVID-19}, year = {2021}, doi = {10.1117/12.2581496}, URL = {https://doi.org/10.1117/12.2581496} } ``` ## Embeddings Visualization of Covid-19 CT scan dataset