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- [ ] Train a binary classifier where 1 class is NIH Chest X Ray images and 2nd class is Google Download images
- [ ] Train a binary classifier where 1 class is NIG chest X Ray images and 2nd class…
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Hi @AlexeyAB & Team ,
I am planning to solve a multi-label problem using YOLOv4.
The problem is to detect the presence and position of catheters and lines on chest x-rays-
[https://www.kaggle.com…
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Suggested by @jzazo
Paper: https://www.nature.com/articles/s41598-018-37638-9
Code: https://github.com/zhaoxuanma/Deeplearning-digital-pathology
Dataset: https://www.nature.com/articles/s41598-018…
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Hi @ieee8023
thank you for maintaining this dataset!
I implemented a [pytorch lightning wrapper for a DenseNet model](https://github.com/oplatek/lightning-Covid19/tree/feature/baseline-model) f…
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Hi,
I'm also a UFSC Araranguá student from course of Information Tecnology and Comunication.
I've experience working with python, data structures, algorithms, database etc.
I'm looking for a…
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Hi, just a very quick question. Chest ImaGenome (https://physionet.org/content/chest-imagenome/1.0.0/) provides very fine-grained labels and bounding boxes for most images in MIMIC-CXR. Do you guys ha…
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Hello,
I have been trying to implement your code as a learning material recently.
However, I haven't achieved the same good results as shown in Figure 3 of your paper.
Could you please help me…
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8th plase: DeepLabV3 with different encoders.
Group Normalization for small batch
Mask threshold (due to bad metric)
Weighted BCE loss for classification-segmentation models.
Ensemble of 3 top we…
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# Bayesian Convolutional Neural Network | Chan`s Jupyter
In this post, we will create a Bayesian convolutional neural network to classify the famous MNIST handwritten digits. This will be a probabili…
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# I performed the following experiment
- Downloaded datasets [1], [2] and [3]
- Extracted PA views for control and pneumonia patients (for [2] all "pneumonia" images were used regardless of the ty…