Accurate Multilevel Classification for Wildlife Images

Table 3

Results for multilevel classification that includes different convolutional backbones, input image resolution, and data augmentation techniques.

ID	Conv. backbone	Resolution	Data augmentation	Top-1	Top-5
MA	DenseNet201	250 × 250	Standard	0.51	0.78
MB	DenseNet201	250 × 250	Central Crop	0.52	0.79
MC	DenseNet201	250 × 250	Multiscale Crop	0.51	0.78
MD	DenseNet201	300 × 300	Standard	0.58	0.83
ME	DenseNet201	300 × 300	Central Crop	0.59	0.84
MF	DenseNet201	300 × 300	Multiscale Crop	0.61	0.85
MG	EfficientNetB5	250 × 250	Standard	0.53	0.82
MH	EfficientNetB5	250 × 250	Central Crop	0.53	0.81
MI	EfficientNetB5	250 × 250	Multiscale Crop	0.54	0.84
MJ	EfficientNetB5	300 × 300	Standard	0.61	0.87
MK	EfficientNetB5	300 × 300	Central Crop	0.62	0.87
ML	EfficientNetB5	300 × 300	Multiscale Crop	0.62	0.88