A new XAI method for point cloud classification uses semantic segmentation to define meaningful perturbation regions and a point-shifting mechanism to compute saliency maps.
Toward Explainable Metrology 4.0: Utilizing Explainable AI to Predict the Pointwise Accuracy of Laser Scanning Devices in Industrial Manufacturing, pages 479–501
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XAI for Point Cloud Data using Perturbations based on Meaningful Segmentation
A new XAI method for point cloud classification uses semantic segmentation to define meaningful perturbation regions and a point-shifting mechanism to compute saliency maps.