
G-CAME, a novel CAM-based XAI method, can efficiently generate concise saliency maps to explain object detection models by utilizing activation maps from selected layers and applying a Gaussian kernel to emphasize critical image regions for the predicted object.


coremsg

gaussian-class-activation-mapping-explainer-efficient-and-concise-explanations-for-object-detection


Gaussian-Class Activation Mapping Explainer: Efficient and Concise Explanations for Object Detection


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A novel black-box explanation method named BODEM is proposed to generate saliency maps that reveal the importance of different parts of an image for object detection models.


model-agnostic-explainable-ai-for-object-detection-in-image-data


Model-Agnostic Explainable AI for Object Detection in Image Data
