dsmil-wsi
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binli123
DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image
Hello, I appreciate very much for your source codes, and I have read your paper carefully and found it very inspiring. But I would like to request you to open...
Thank you very much for the Pre-computed features of Camelyon16 datasets provided in your code(https://uwmadison.box.com/shared/static/l9ou15iwup73ivdjq0bc61wcg5ae8dwe.zip). What I would like to ask you is on which WSI magnification scale is this...
Hello, I tested on my own binary data set. After simclr (batch_size=256) feature extraction, I found that my training accuracy has been hovering around 60%, and finally it will even...
Hello, can you tell me if the batchsize must be greater than 512 when extracting image features under simclr?
Hello, author. When I used your network to train my own WSI, simclr trained 200 epochs. My data is divided into positive and negative, so I set number_ class=1. But...
Hi, I want to use your pre-trained ResNet models, but I could not find which transforms you used. To be more precise, when using ImageNet pre-trained models on new inputs,...
I have a question, your simlr is pre-training, does it include all the data of camelyon16 (training set and test set)? Because I found that your feature extractor is faulty,...
Hi @binli123, Given the data obtained as #39, I extracted the features using both model-v0 and model-v2. The differences between their performances on the downstream task are evident. Here is...
Hi @binli123 , I'm trying to replicate your results without success on camelyon16. I put the number of classes to 1 and also tried weights online for computing the feats...
HI, I am trying to reproduce your results for Camelyon 16. Can you please confirm the settings for features creation? I am using deepzoom_tiler.py with following settings: parser.add_argument('-d', '--dataset', type=str,...
