XAI analysis identifies high visual similarity across colony cardinality classes as the primary limit on MicrobiaNet performance in bacterial colony counting, revising prior model assessments.
Li- bra R-CNN: Towards Balanced Learning for Object Detection, in: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp
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Investigation of cardinality classification for bacterial colony counting using explainable artificial intelligence
XAI analysis identifies high visual similarity across colony cardinality classes as the primary limit on MicrobiaNet performance in bacterial colony counting, revising prior model assessments.