Rack detection Computer Vision Project

Cognitica AI

Updated 2 years ago

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Classes (5)
Description

Here are a few use cases for this project:

  1. Warehouse Management: The Rack Detection model can be applied to rapidly identify and catalog different types of racks in a warehouse alongside objects on the racks, enhancing the inventory management process.

  2. Safety Compliance: In areas where forklifts and people are active, this model can distinguish different classes of objects and preemptively warn against potential safety hazards.

  3. Retail Inventory Tracking: The model can be used in retail stores for tracking stock on racks, identifying missing items, and optimizing the restocking procedure.

  4. Construction Review: It can be employed in construction and renovation projects to detect and classify types of racks, helping in planning, designing, and efficient utilization of space.

  5. Automated Robotics: Robotics in warehouses can use this model to identify and navigate towards specific types of racks or items on the rack, thereby improving efficiency in pick-and-place tasks.

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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{
                            rack-detection-bv6iz_dataset,
                            title = { Rack detection Dataset },
                            type = { Open Source Dataset },
                            author = { Cognitica AI },
                            howpublished = { \url{ https://universe.roboflow.com/cognitica-ai-llbx4/rack-detection-bv6iz } },
                            url = { https://universe.roboflow.com/cognitica-ai-llbx4/rack-detection-bv6iz },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-11-23 },
                            }
                        
                    

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