IndraLab

Statements

CALM1 binds HR. 9 / 9
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sparser
"Generalized CAM methods, like Grad-CAM [ xref ], Grad-CAM++ [ xref ], Score-CAM [ xref ], Poly-CAM [ xref ], and HR-CAM [ xref ], explore the decision-making of an arbitrary CNN."
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"For examples, two particular CAMS, the Gradient Weighted CAM (Grad-CAM) and High Resolution CAM (HR-CAM) have been shown to provide insights into the process of AI decision-making for oral cancer and other cancer types, with improved diagnostic performance and positive user feedback ( xref – xref )."
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sparser
"We applied Explainable AI techniques, namely Grad-CAM and HR-CAM, to both networks and explored important features that contributed to their decisions."
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sparser
"Additionally, we aimed to explore which features were responsible for both networks’ decisions, using the two Explainable AI methods Grad-CAM [ xref ] and HR-CAM [ xref ]."
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"The techniques Grad-CAM and HR-CAM were used to create visual explanations."
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"Another limitation relates to the use of HR-CAM for the segmentation network."
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"HR-CAM relies on adding a global average pooling layer and a dense layer on top of the trained network [ xref ]."
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"For explaining the predictions of a segmentation network, Grad-CAM is more suitable than HR-CAM."
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"Specifically, Grad-CAM generates heatmaps by computing the gradients of the target class score with respect to the feature maps of the last convolutional layers in the CNN while HR-CAM aggregates feature maps from several layers to create a high-resolution localization map ( xref )."
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