Table 2.

Table of evaluation results for each model for view classification

Model	Train Accuracy	Test Accuracy	Training Time/Epoch
CNN	95.39%	92.05% (+/−0.72)	919 s
CNN with Segmentation	95.18%	93.64% (+/−0.61)	903 s
Resnet50*	92.61%	91.36% (+/−1.43)	7482 s
VGG16*	98.15%	83.67% (+/−2.68)	4559 s
			(second stage)
Ensemble	—	94.40% (+/−0.52)	—

Highest performing model by overall test accuracy is an ensemble of three CNN models with field of view segmentation, while transfer learning from Resnet50 and VGG16 models yielded lower test accuracies compared to a single CNN model.