@inproceedings{4f76a9d73b234147a851e82850d8bf20,
title = "CNN-Based Boat Detection Model for Alert System Using Surveillance Video Camera",
abstract = "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.",
keywords = "Boat classification, Boat detection, Convolutional Neural Networks, Image Recognition, Surveillance Video Camera",
author = "Tatsuhiro Akiyama and Yosuke Kobayashi and Jay Kishigami and Kenji Muto",
year = "2018",
month = dec,
day = "12",
doi = "10.1109/GCCE.2018.8574704",
language = "English",
series = "2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "758--759",
booktitle = "2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018",
note = "7th IEEE Global Conference on Consumer Electronics, GCCE 2018 ; Conference date: 09-10-2018 Through 12-10-2018",
}