Author of paper: Mark Sandler Andrew Howard Menglong Zhu Andrey Zhmoginov Liang-Chieh Chen Google Inc.

Abstract

In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models.

Introduction

The drive to improve accuracy often comes at a cost: modern state of the art networks require high computational resources beyond the capabilities of many mobile and embedded applications.

This paper introduces a new neural network architecture that is specifically tailored for mobile and resource constrained environments, by significantly decreasing the number of operations and memory needed while retaining the same accuracy.