GPR-Training-3 Computer Vision Project

Ege Yüceel

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Description

Here are a few use cases for this project:

  1. Scrap Sorting: The model could be used in waste management facilities for the sorting of metal and non-metal scrap materials. This could streamline recycling processes by identifying and separating materials into appropriate categories.

  2. Quality Control in Manufacturing: Manufacturers of goods that specifically require metallic or non-metallic materials might use the model for quality control, to ensure that only the right type of material is used in production.

  3. Archaeological Analysis: Archaeologists could use this model to assist in the analysis and identification of artifacts, distinguishing between metal and non-metal items.

  4. Mining Industry: Industrial mining firms might find use in identifying and categorizing excavated materials based on their metallic properties, helping to maximize the efficiency and potential yield of dig sites.

  5. Retail: Businesses that sell metal and non-metal materials or products could use the model to automate the inventory management process, significantly reducing the manpower needed for warehouse management.

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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{
                            gpr-training-3_dataset,
                            title = { GPR-Training-3 Dataset },
                            type = { Open Source Dataset },
                            author = { Ege Yüceel },
                            howpublished = { \url{ https://universe.roboflow.com/ege-yuceel/gpr-training-3 } },
                            url = { https://universe.roboflow.com/ege-yuceel/gpr-training-3 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { dec },
                            note = { visited on 2024-09-24 },
                            }
                        
                    

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