cable_length_segmentation Computer Vision Project

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Classes (7)
Cable
Clip_Down
Clip_Lateral
Clip_Up
Head_1
Head_Black
Head_Blue
Description

Here are a few use cases for this project:

  1. Industrial Inspection and Maintenance: This model can be used by manufacturing industries, especially those dealing with a large number of cables. It can identify and classify different parts of cables, helping to improve efficiency in checking their lengths, locations, and usage, reducing manual labor significantly.

  2. Electronics Manufacturing: It can serve as an important tool for quality control in electronics production. By identifying cable-length classes and their respective parts, manufacturers can ensure that the correct parts have been attached and cables have been modified to the intended size, helping to prevent production errors.

  3. Networking and Telecommunication: In networking, there are many different cables with different heads and clips. This model could be used to identify and classify these cables, assisting in network setup and maintenance, making it faster, safer, and more efficient.

  4. Recycling & Waste Management: This model can be applied in facilities where electronics are dismantled for recycling. It can automate the process of identifying and sorting cables and their parts, leading to efficient waste management and improving the recovery of valuable materials.

  5. Education and Training: It can be used as an educational tool for students and professionals in electronics, networking, or related fields. They can interact with an AI tool that can accurately classify different parts of cables, facilitating learning about different cable parts and their respective properties.

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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{
                            cable_length_segmentation_dataset,
                            title = { cable_length_segmentation Dataset },
                            type = { Open Source Dataset },
                            author = { class },
                            howpublished = { \url{ https://universe.roboflow.com/class-lvbe6/cable_length_segmentation } },
                            url = { https://universe.roboflow.com/class-lvbe6/cable_length_segmentation },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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