Name: forklift-ameise Dataset
License: https://creativecommons.org/licenses/by/4.0/

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Explore Dataset

Here are a few use cases for this project:

Warehouse Management: This computer vision model can be employed to monitor and manage inventory in large warehouses or storage facilities. It could detect and track various types of forklifts (ins, ameise, ylk-yok, ksk-yok), as well as items like grey-palets, improving efficiency and preventing misplacement.
Construction Site Safety: Applying this model can guide in ensuring safety at construction sites. Detecting elements such as forklifts, is-makinası, kamyon, and workers (CgOnFace) and assessing their interactions could prevent accidents and enhance efficiency.
Logistics and Supply Chain: In a supply chain scenario, this model could be used for loading and unloading goods. It would recognize different classes like forklifts, palets, kamyon, and help streamline the logistics process by organizing and tracking the movement of these elements.
Automated Forklift Systems: This model could be used in developing automated forklift driving systems. Recognizing different elements in a warehouse (including forklift, palet, kamyon, etc.), it would aid in smart navigation, avoiding collisions and increasing productivity.
Advanced Surveillance: Surveillance in industrial settings can be optimized using this model. By identifying forklifts, kamyon, and people (CgOnFace), it can provide real-time alerts about unauthorized activities or potential dangerous situations. The model can also help to monitor employee productivity by tracking machinery usage.

Cite This Project

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

@misc{
                            forklift-ameise_dataset,
                            title = { forklift-ameise Dataset },
                            type = { Open Source Dataset },
                            author = { First },
                            howpublished = { \url{ https://universe.roboflow.com/first-psddo/forklift-ameise } },
                            url = { https://universe.roboflow.com/first-psddo/forklift-ameise },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-04-25 },
                            }