OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 21.03.2026, 02:27

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

M3d-CAM: A PyTorch library to generate 3D data attention maps for medical deep learning

2020·0 Zitationen·arXiv (Cornell University)Open Access
Volltext beim Verlag öffnen

0

Zitationen

4

Autoren

2020

Jahr

Abstract

M3d-CAM is an easy to use library for generating attention maps of CNN-based PyTorch models improving the interpretability of model predictions for humans. The attention maps can be generated with multiple methods like Guided Backpropagation, Grad-CAM, Guided Grad-CAM and Grad-CAM++. These attention maps visualize the regions in the input data that influenced the model prediction the most at a certain layer. Furthermore, M3d-CAM supports 2D and 3D data for the task of classification as well as for segmentation. A key feature is also that in most cases only a single line of code is required for generating attention maps for a model making M3d-CAM basically plug and play.

Ähnliche Arbeiten

Autoren

Themen

COVID-19 diagnosis using AIAdvanced Neural Network ApplicationsArtificial Intelligence in Healthcare and Education
Volltext beim Verlag öffnen