MobileNetV2: Inverted Residuals and Linear Bottlenecks

Benchmark Model Rank Results
retinal-oct-disease-classification-on-srinivasan2014MobileNet-v2#7Acc: 97.46
retinal-oct-disease-classification-on-oct2017MobileNet-v2#8Acc: 98.5Sensitivity: 99.4
semantic-segmentation-on-dada-segMobileNetV2#27mIoU: 16.05
image-classification-on-cifar-10Mobile Net_Sam#159Percentage correct: 95.50
object-detection-on-coco-test-devMobileNetV2 + SSDLite#192box mAP: 22.1
image-classification-on-imagenetMobileNetV2 (1.4)#1012Top 1 Accuracy: 74.7%Number of params: 6.9MGFLOPs: 1.170
image-classification-on-imagenetMobileNetV2#1054Top 1 Accuracy: 72%Number of params: 3.4MGFLOPs: 0.600