Laue-diffraction Computer Vision Project

Yolo

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Description

Here are a few use cases for this project:

  1. Metallurgy Industry: The "Laue-diffraction" model could be used in the metallurgy industry for crystallography. It can analyze the distribution and types of diffraction spots in metals to understand its crystal structure and properties. It could be hugely beneficial for quality control and material innovation.

  2. Astronomy/Space Research: The dataset could be used by space researchers and astronomers to identify and analyze the microscopic structure of meteors and other celestial bodies from the captured images, improving our understanding of cosmic materials.

  3. Earth Science/Paleontology: The model could be used to analyze fossil or rock samples. It would bring great insight into the geological and ecological history encoded in these samples, facilitating researches into earth's past.

  4. Materials Science Research: Material scientists could use this model to study and evaluate the growth of crystal lattices in various materials. It could also assist in exploring new materials or optimizing existing ones for different applications.

  5. Pharmaceutical Industry: In the pharmaceutical industry, understanding of crystal structures is crucial while formulating new medicines and drugs. The model could be helpful in analyzing crystalline substances used in medications, influencing the effectiveness and stability of drug products.

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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{
                            laue-diffraction_dataset,
                            title = { Laue-diffraction Dataset },
                            type = { Open Source Dataset },
                            author = { Yolo },
                            howpublished = { \url{ https://universe.roboflow.com/yolo-ucvuc/laue-diffraction } },
                            url = { https://universe.roboflow.com/yolo-ucvuc/laue-diffraction },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-09-29 },
                            }
                        
                    

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