MobileNetV2: Inverted Residuals and Linear Bottlenecks

Benchmark Model Rank Results
image-classification-on-cifar-10Mobile Net_Sam#130Percentage correct: 95.50
image-classification-on-imagenetMobileNetV2 (1.4)#908Top 1 Accuracy: 74.7%Number of params: 6.9MGFLOPs: 1.170
image-classification-on-imagenetMobileNetV2#940Top 1 Accuracy: 72%Number of params: 3.4MGFLOPs: 0.600
retinal-oct-disease-classification-onMobileNet-v2#7Acc: 97.46
retinal-oct-disease-classification-on-oct2017MobileNet-v2#8Acc: 98.5Sensitivity: 99.4
semantic-segmentation-on-dada-segMobileNetV2#27mIoU: 16.05