PIV_avance2 Computer Vision Project

Clase PIV

Updated 2 years ago

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Classes (7)
Bus
Camión
Moto
Particular
Taxi Van
Vehículos no motorizados
Description

Here are a few use cases for this project:

  1. Traffic Analysis and Management: PIV_avance2 can be used by traffic control authorities to monitor, analyze, and manage traffic flow on roads or highways. The model can differentiate between vehicle types, helping authorities to better understand traffic patterns and implement effective traffic management strategies.

  2. Logistics and Fleet Management: Companies with large fleets of vehicles, such as delivery services or public transportation agencies, can utilize PIV_avance2 to monitor their vehicles and optimize their operations. The model can help track various vehicle types, plan routes, and allocate resources more efficiently.

  3. Parking and Access Control: PIV_avance2 can be implemented in parking facilities or restricted areas to automate access control based on vehicle types. For example, the model can help enforce specific parking areas designated for different vehicles like taxis, buses, or motorcycles.

  4. Intelligent Transportation Systems (ITS): PIV_avance2 can serve as a component in ITS by providing real-time information about vehicle types on roads. This information can be used to improve traffic signal timing, adapt speed limits, and optimize road infrastructure, ultimately enhancing road safety and mobility.

  5. Urban Planning and Infrastructure Design: The PIV_avance2 model can be used by urban planners and civil engineers to analyze vehicular patterns across different regions within a city. The insights gained from this analysis can guide the design and development of more efficient transportation infrastructure, such as public transit systems, bike lanes, and pedestrian-friendly zones.

Supervision

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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{
                            piv_avance2_dataset,
                            title = { PIV_avance2 Dataset },
                            type = { Open Source Dataset },
                            author = { Clase PIV },
                            howpublished = { \url{ https://universe.roboflow.com/clase-piv/piv_avance2 } },
                            url = { https://universe.roboflow.com/clase-piv/piv_avance2 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-11-16 },
                            }