MobileACNet: ACNet-Based Lightweight Model for Image Classification

Tao Jiang, Ming Zong, Yujun Ma, Feng Hou, Ruili Wang

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Lightweight CNN models aim to extend the application of deep learning from conventional image classification to mobile edge device-based image classification. However, the accuracy of lightweight CNN models currently is not as comparable as traditional large CNN models. To improve the accuracy of mobile platform-based image classification, we propose MobileACNet, a novel ACNet-based lightweight model based on MobileNetV3 (a popular lightweight CNN for image classification on mobile platforms). Our model adopts a similar idea to ACNet: consider global inference and local inference adaptively to improve the classification accuracy. We improve the MobileNetV3 by replacing the inverted residual block with our proposed adaptive inverted residual module (AIR). Experimental results show that our proposed MobileACNet can effectively improve the image classification accuracy by providing additional adaptive global inference on three public datasets, i.e., Cifar-100 dataset, Tiny ImageNet dataset, and a large-scale dataset ImageNet, for mobile-platform-based image classification.

Original languageEnglish
Title of host publicationImage and Vision Computing - 37th International Conference, IVCNZ 2022, Revised Selected Papers
EditorsWei Qi Yan, Minh Nguyen, Martin Stommel
PublisherSpringer Science and Business Media Deutschland GmbH
Pages361-372
Number of pages12
ISBN (Print)9783031258244
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event37th International Conference on Image and Vision Computing New Zealand, IVCNZ 2022 - Auckland, New Zealand
Duration: 24 Nov 202225 Nov 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13836 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference37th International Conference on Image and Vision Computing New Zealand, IVCNZ 2022
Country/TerritoryNew Zealand
CityAuckland
Period24/11/2225/11/22

Keywords

  • Adaptive global inference
  • Lightweight CNN models
  • Mobile-platform-based image classification
  • MobileACNet

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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