End-to-End Asbestos Roof Detection on Orthophotos Using Transformer-Based YOLO Deep Neural Network-Reference-Cited by-同舟云学术

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End-to-End Asbestos Roof Detection on Orthophotos Using Transformer-Based YOLO Deep Neural Network

Published:2023 Issue: Volume: Page:232-244
ISSN:0302-9743
Container-title:Image Analysis and Processing – ICIAP 2023
language:
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Author:

Pace Cesare Davide^ORCID,Bria Alessandro^ORCID,Focareta Mariano^ORCID,Lozupone Gabriele^ORCID,Marrocco Claudio^ORCID,Meoli Giuseppe^ORCID,Molinara Mario^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43148-7_20

Reference27 articles.

1. National Toxicology Program. RoC Profile: Asbestos; 15th RoC (2021). https://ntp.niehs.nih.gov/ntp/roc/content/profiles/asbestos.pdf

2. World Health Organization. Asbestos: elimination of asbestos-related diseases, 15 February 2018. https://www.who.int/news-room/fact-sheets/detail/asbestos-elimination-of-asbestos-related-diseases

3. Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. arXiv preprint arXiv:1506.02640 (2015)

4. Jocher, G.: ultralytics/yolov5: v3.1 - bug fixes and performance improvements. Zenodo, October 2020. https://doi.org/10.5281/zenodo.4154370

5. Vaswani, A.: Attention is all you need. arXiv preprint arXiv:1706.03762 (2017)

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1. Motion perception-driven multimodal self-supervised video object segmentation;The Visual Computer;2024-08-09

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