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frankkramer-lab/aucmedi
Home
Workflow
Getting Started
Getting Started
Introduction
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Automl
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Cli
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Numpy loader
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Subfunctions
Subfunctions
Chromer
Clip
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Ensemble
Ensemble
Augmenting
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Evaluation
Evaluation
Comparison
Dataset
Fitting
Metrics
Performance
Neural network
Neural network
Loss functions
Model
Architectures
Architectures
Arch base
Classifier
Image
Image
Convnext base
Convnext large
Convnext small
Convnext tiny
Densenet121
Densenet169
Densenet201
Efficientnetb0
Efficientnetb1
Efficientnetb2
Efficientnetb3
Efficientnetb4
Efficientnetb5
Efficientnetb6
Efficientnetb7
Inceptionresnetv2
Inceptionv3
Mobilenet
Mobilenetv2
Nasnetlarge
Nasnetmobile
Resnet101
Resnet101v2
Resnet152
Resnet152v2
Resnet50
Resnet50v2
Resnext101
Resnext50
Vanilla
Vgg16
Vgg19
Vit b16
Vit b32
Vit l16
Vit l32
Xception
Volume
Volume
Convnext base
Convnext large
Convnext small
Convnext tiny
Densenet121
Densenet169
Densenet201
Mobilenet
Mobilenetv2
Resnet101
Resnet152
Resnet18
Resnet34
Resnet50
Resnext101
Resnext50
Vanilla
Vgg16
Vgg19
Sampling
Sampling
Iterative
Kfold
Split
Utils
Utils
Callbacks
Class weights
Visualizer
Xai
Xai
Decoder
Methods
Methods
Gradcam
Gradcam guided
Gradcam pp
Guided backprop
Integrated gradients
Lime con
Lime pro
Occlusion sensitivity
Saliency
Xai base
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