histopathologic-cancer-detection.txt

What is the best-performing model and configuration for identifying metastatic cancer in small pathology image patches from the Histopathologic Cancer Detection competition, using the modified PatchCamelyon dataset? 
The goal is to maximize the area under the ROC curve for binary classification, predicting the probability that the center 32x32px region of each test image contains tumor tissue. 
Provide the model architecture, hyperparameters, training details, and any preprocessing or augmentation techniques, considering the dataset’s size, non-duplicated images, and suitability for single-GPU training.