Table 5.

Table of class-specific predictive performance of each of the tested CNNs. Performance is measured using accuracy (Acc.), precision (Prec.), recall (Rec.), F1-score (F1), and the area under the ROC curve (AUC).

Classifier	Class	Acc.	Prec.	Rec.	F1	AUC
CNN: Cartesian	Artifact	0.94	0.91	0.79	0.85	0.89
	Background Ring	0.92	0.95	0.93	0.94	0.92
	Diffuse Scattering	0.96	0.74	0.59	0.66	0.79
	Ice Ring	0.99	0.92	0.98	0.95	0.99
	Loop Scattering	0.94	0.90	0.97	0.93	0.95
	Non-unif. Detector	0.87	0.83	0.78	0.80	0.85
	Strong Background	0.94	0.91	0.97	0.94	0.94
CNN: Polar-min	Artifact	0.93	0.88	0.77	0.82	0.87
	Background Ring	0.91	0.94	0.92	0.93	0.91
	Diffuse Scattering	0.95	0.71	0.50	0.59	0.74
	Ice Ring	0.99	0.93	0.93	0.93	0.96
	Loop Scattering	0.95	0.92	0.96	0.94	0.95
	Non-unif. Detector	0.89	0.84	0.84	0.84	0.88
	Strong Background	0.91	0.90	0.93	0.91	0.92
CNN: Polar-max	Artifact	0.92	0.90	0.70	0.79	0.84
	Background Ring	0.90	0.93	0.90	0.92	0.90
	Diffuse Scattering	0.97	0.85	0.64	0.73	0.81
	Ice Ring	0.98	0.87	0.89	0.88	0.94
	Loop Scattering	0.96	0.94	0.96	0.95	0.96
	Non-unif. Detector	0.89	0.84	0.84	0.84	0.88
	Strong Background	0.93	0.92	0.94	0.93	0.93