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CNN saliency maps for regression problems
2019 Community Moderator ElectionRandom Forest Regression. How to represent really long list of categories for processingHow to select regression algorithm for noisy (scattered) data?Regression coefficient stability measurement in a multiple linear regression particularly in r?What are the advantages/disadvantages of using Autoencoders over CNNs for image search?Are non-zero paddings used?How to improve a regression prediction model for data with parameters which are out of sample range?Data Augmentation for RegressionHow to do semi-supervised learning for regressionCommon Techniques to Generate from a Regression Neural Network ModelAlternatives to linear activation function in regression tasks to limit the output
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I've been using CNNs for regression tasks. While I know there are techniques such as integrated gradients and guided backpropogation to generate saliency maps, most examples generate saliency maps only for classification problems. I would like to ask if there are methods which can generate saliency maps for regression problems? Namely, I'd like to figure out which regions of the image are responsible for the final regression output, so that I can conduct some ablation studies. Are there any existing methods/code which I can apply?
regression convnet predictor-importance image
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I've been using CNNs for regression tasks. While I know there are techniques such as integrated gradients and guided backpropogation to generate saliency maps, most examples generate saliency maps only for classification problems. I would like to ask if there are methods which can generate saliency maps for regression problems? Namely, I'd like to figure out which regions of the image are responsible for the final regression output, so that I can conduct some ablation studies. Are there any existing methods/code which I can apply?
regression convnet predictor-importance image
New contributor
resonance20 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I've been using CNNs for regression tasks. While I know there are techniques such as integrated gradients and guided backpropogation to generate saliency maps, most examples generate saliency maps only for classification problems. I would like to ask if there are methods which can generate saliency maps for regression problems? Namely, I'd like to figure out which regions of the image are responsible for the final regression output, so that I can conduct some ablation studies. Are there any existing methods/code which I can apply?
regression convnet predictor-importance image
New contributor
resonance20 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I've been using CNNs for regression tasks. While I know there are techniques such as integrated gradients and guided backpropogation to generate saliency maps, most examples generate saliency maps only for classification problems. I would like to ask if there are methods which can generate saliency maps for regression problems? Namely, I'd like to figure out which regions of the image are responsible for the final regression output, so that I can conduct some ablation studies. Are there any existing methods/code which I can apply?
regression convnet predictor-importance image
regression convnet predictor-importance image
New contributor
resonance20 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
resonance20 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
resonance20 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 20 at 16:19
resonance20resonance20
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resonance20 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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