Original paper
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Published: Jun 1, 2018
Abstract
In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of different model sizes. We also describe efficient ways of applying these mobile models to object detection in a novel framework we call SSDLite. Additionally, we demonstrate how to build mobile semantic segmentation models through a reduced form of...
Paper Details
Title
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Published Date
Jun 1, 2018
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