PalletDetection Computer Vision Project

Institute Technology Bandung

Updated 2 years ago

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Classes (2)
pallet_hole
pallet_stack
Description

Here are a few use cases for this project:

  1. Warehouse Inventory Management: PalletDetection can be used to automate the tracking and management of pallets in warehouses or storage facilities, allowing users to monitor the status of pallets with different classes, such as pallet_hole and pallet_stack. This can improve inventory control, reduce manual labor, and minimize errors.

  2. Forklift Automation: PalletDetection can be integrated into forklifts and other material handling systems to enable autonomous navigation and pallet manipulation. By identifying the pallet classes, these systems can be programmed to safely and efficiently move or stack pallets, improving warehouse productivity.

  3. Pallet Sorting and Repair: PalletDetection can be utilized in pallet recycling and repair centers to identify damaged or defective pallets. By quickly identifying pallet_hole or pallet_stack problems, these centers can streamline the repair and sorting process, optimizing their operations.

  4. Supply Chain Optimization: PalletDetection can be used by logistics and transportation companies to track and manage the flow of goods within their supply chains. By identifying pallet classes such as pallet_hole or pallet_stack, they can optimize their storage and distribution processes to reduce operational costs and improve overall efficiency.

  5. Safety and Security Surveillance: PalletDetection can be integrated into security cameras and monitoring systems in warehouses and other industrial settings. By identifying potential hazards such as unsupported pallet_stacks or unstable pallet_hole arrangements, the model can help prevent accidents and ensure proper safety protocols are followed.

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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{
                            palletdetection_dataset,
                            title = { PalletDetection Dataset },
                            type = { Open Source Dataset },
                            author = { Institute Technology Bandung },
                            howpublished = { \url{ https://universe.roboflow.com/institute-technology-bandung-yqpmf/palletdetection } },
                            url = { https://universe.roboflow.com/institute-technology-bandung-yqpmf/palletdetection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { sep },
                            note = { visited on 2024-11-14 },
                            }
                        
                    

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