old building damage detection Computer Vision Project

ive

Updated 2 years ago

1k

views

56

downloads
Classes (3)
1
Crack
concrete spalling
Description

Here are a few use cases for this project:

  1. Historical Building Restoration: Architects and restorers can use this model to detect and categorize damage to historical buildings. It can be an important element in planning restoration efforts while preserving the original structure.

  2. Real Estate & Building Inspection: Real estate agents and building inspectors can use this model to identify potential property damages during inspections. It can facilitate quicker and more accurate evaluations, leading to better appraisal and risk assessments for buyers, sellers, and insurers.

  3. Infrastructure Management: Municipal or city administrators can use this model to inspect the health of public infrastructure like bridges, flyovers, or tunnels. This can help in timely maintenance, preventing potential accidents and ensuring safety.

  4. Earthquake/Flood Damage Assessment: Post-disaster recovery organizations could use this model to quickly assess the structural damage after earthquakes or floods, helping to decide whether buildings are safe for habitation or require demolition, aiding in effective resource allocation.

  5. Insurance Claim Processing: Insurance firms can leverage this algorithm to verify and process claims related to structural damage. The model can confirm the type of damage and it's extent, hence automating and expediting claim validations.

Supervision

Build Computer Vision Applications Faster with Supervision

Visualize and process your model results with our reusable computer vision tools.

Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            old-building-damage-detection_dataset,
                            title = { old building damage detection Dataset },
                            type = { Open Source Dataset },
                            author = { ive },
                            howpublished = { \url{ https://universe.roboflow.com/ive-qdohl/old-building-damage-detection } },
                            url = { https://universe.roboflow.com/ive-qdohl/old-building-damage-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-11-21 },
                            }