CNN-Based Boat Detection Model for Alert System Using Surveillance Video Camera

Tatsuhiro Akiyama, Yosuke Kobayashi, Jay Kishigami, Kenji Muto

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

In Tokyo, various boats pass through the canal on the bayside. The loud sound created by these boats may cause some stress to the residents in that area. We propose a boat detection model based on convolutional neural networks (CNNs) using VGG19 that is trained using several types of boat pictures. Our proposed model aims to detect the type of boat passing through the canal using images obtained from the surveillance video camera. We finally achieve a practical result as F1-score of 0.70 by the proposed model.

本文言語English
ホスト出版物のタイトル2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ758-759
ページ数2
ISBN(電子版)9781538663097
DOI
出版ステータスPublished - 2018 12 12
イベント7th IEEE Global Conference on Consumer Electronics, GCCE 2018 - Nara, Japan
継続期間: 2018 10 92018 10 12

出版物シリーズ

名前2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018

Other

Other7th IEEE Global Conference on Consumer Electronics, GCCE 2018
国/地域Japan
CityNara
Period18/10/918/10/12

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学
  • 安全性、リスク、信頼性、品質管理
  • 器械工学

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