Display_dataset Semantic Segmentation Dataset and Pre-Trained Model by OD

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Explore Dataset

Here are a few use cases for this project:

Manufacturing Quality Control: The "Display_dataset" computer vision model can be used in manufacturing units for automated inspection and quality control to identify defective objects, helping to improve the efficiency and accuracy of defect detection processes.
E-Commerce Product Inspection: The model could be employed in e-commerce distribution centers to inspect products for defects prior to shipping, reducing return rates due to damaged goods and increasing overall customer satisfaction.
Food Industry Inspection: The system can be used in the food industry to identify defective items such as misshapen fruits, vegetables, or damaged packaged goods.
Automotive Industry: In the automotive industry, this model can be used to identify defects in assembled parts and ensure that each component is properly taken care of before the final assembly.
Textile Industry: The "Display_dataset" computer vision model can be used in textile manufacturing to detect defects in material or the final product, avoiding the cost and waste of defective goods.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            display_dataset_dataset,
                            title = { Display_dataset Dataset },
                            type = { Open Source Dataset },
                            author = { OD },
                            howpublished = { \url{ https://universe.roboflow.com/od-hyotr/display_dataset } },
                            url = { https://universe.roboflow.com/od-hyotr/display_dataset },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-04-29 },
                            }