@inproceedings{c4dcb6ffb7c348638f895a514ded5c49,
title = "Integrated Compressed Sensing and YOLOv4 for Application in Image-storage and Object-recognition of Dashboard Camera",
abstract = "This paper focuses on the research of the dashboard camera for improving the storage space and object recognition. The experiments showed that the CS method of ISTA-Net (Iterative Shrinkage Thresholding Algorithm with Network) can reduce the storage space by at least 60% and without obviously sacrificing the image quality. Furthermore, the recognition method by YOLOv4 can overcome the variety of environments, which can reach the recognition ratio of over 80% in a small 480x480 pixels. The recognition function can help to quickly catch the key features (ex: car, traffic signal, pedestrian, etc.) in the storage data of the dashboard camera.",
author = "Wu, {Jim Wei} and Wu, {Cheng Chia} and Cen, {Wen Shan} and Chao, {Shao An} and Weng, {Jui Tse}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 Australian and New Zealand Control Conference, ANZCC 2021 ; Conference date: 25-11-2021 Through 26-11-2021",
year = "2021",
doi = "10.1109/ANZCC53563.2021.9628221",
language = "???core.languages.en_GB???",
series = "2021 Australian and New Zealand Control Conference, ANZCC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7--11",
booktitle = "2021 Australian and New Zealand Control Conference, ANZCC 2021",
}