new_yaotian Computer Vision Project

杜昊晨

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Classes (6)
aokeng
diaoqi
xianxinglashang
xiaotousunshang
yinhuasunshang
zhuangqi
Description

Here are a few use cases for this project:

  1. Industrial Quality Control: The new_yaotian model can be used in various industries such as manufacturing, textiles, and automotive, where it can help in identifying different types of defects in the production process. This would lead to improved product quality and less wastage.

  2. Archaeology and Art restoration: This model can assist archaeologists or art restorers in the identification of deteriorations and damages on artifacts or paintings such as "zhuangqi" or "diaoqi", facilitating in the restoration process.

  3. Agriculture: The new_yaotian model can be used in agriculture for identifying diseases or defects in crops, thus helping take corrective actions early, resulting in improved crop health and yield.

  4. Photo Restoration: In the field of photography and film, this model could be instrumental in identifying and categorizing various types of damages in vintage or old photographs/films, which can further aid in their restoration.

  5. Healthcare: This model can contribute to performing examination of medical images such as X-Rays or CT scans, helping in the identification of certain defect classes, thus assisting doctors with diagnosis. It's important to notice that this would require an extremely high level of accuracy and reliability.

Supervision

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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{
                            new_yaotian_dataset,
                            title = { new_yaotian Dataset },
                            type = { Open Source Dataset },
                            author = { 杜昊晨 },
                            howpublished = { \url{ https://universe.roboflow.com/-yttj2/new_yaotian } },
                            url = { https://universe.roboflow.com/-yttj2/new_yaotian },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { apr },
                            note = { visited on 2024-12-22 },
                            }
                        
                    

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