Cracks Computer Vision Project
Updated a year ago
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This was used in our research paper that focuses on addressing the critical need for efficient and accurate detection of cracks in buildings. With the prevalence of seismic activity posing substantial risks to structural integrity, manual inspection methods prove time-consuming and subjective and could result in necessitating the development of an automated solution. By utilizing datasets from Kaggle and Roboflow Universe, the research outlines the methodology involving data understanding, preparation, and modeling processes, culminating in the integration of the best-performing YOLOv8 model into an interactive interface.
Note:
The 3,000 images in this dataset are manually annotated by the researchers, and the rest are cloned with annotated images already.
Contributors:
- Lape, Sarah Mae S.
- Mesa, Apollo Niel R.
- Pabi, Christopher Kent A.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
cracks-bmeqe_dataset,
title = { Cracks Dataset },
type = { Open Source Dataset },
author = { SS },
howpublished = { \url{ https://universe.roboflow.com/ss-bxmah/cracks-bmeqe } },
url = { https://universe.roboflow.com/ss-bxmah/cracks-bmeqe },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { jan },
note = { visited on 2024-12-21 },
}