Multi-Connection of Double Residual Block for YOLOv5 Object Detection

Cheng Lin Li, Chung Yen Su

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a different method of deepening the network model of YOLOv5s6 and design three types of Multi-Connection (MC) blocks that are suitable for specific datasets. The main purpose of Multi-Connection block is to reuse features and retain input features for passing down. Eight public datasets and one customized dataset are experimented for verification. We improve the residual block in YOLOv5. The results show that the average precision (AP) can be increased. Compared with the YOLOv5s6, YOLOv5s6 with MC type I increases the AP by 1.6% in the Global Wheat Head Dataset 2020, YOLOv5s6 with MC type II increases the AP by 2.9% in the PlanDoc dataset, and YOLOv5s6 with MC type III increases the AP by 2.9% in the PASCAL Visual Object Classes (VOC) dataset. Using the multi-connection of double residual block performs better than the original residual block of YOLOv5s6.

Original languageEnglish
Title of host publicationProceedings of the 2022 8th International Conference on Applied System Innovation, ICASI 2022
EditorsShoou-Jinn Chang, Sheng-Joue Young, Artde Donald Kin-Tak Lam, Liang-Wen Ji, Stephen D. Prior
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13-16
Number of pages4
ISBN (Electronic)9781665496506
DOIs
Publication statusPublished - 2022
Event8th International Conference on Applied System Innovation, ICASI 2022 - Nantou, Taiwan
Duration: 2022 Apr 212022 Apr 23

Publication series

NameProceedings of the 2022 8th International Conference on Applied System Innovation, ICASI 2022

Conference

Conference8th International Conference on Applied System Innovation, ICASI 2022
Country/TerritoryTaiwan
CityNantou
Period2022/04/212022/04/23

Keywords

  • Multi-Connection block
  • Object detection
  • Residual block
  • YOLOv5

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Control and Optimization

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