als_bATCH2 Computer Vision Project

Leela Kantheti

Updated 3 years ago

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Description

Here are a few use cases for this project:

  1. Traffic Monitoring: This model can be utilized by city traffic control departments to automate vehicle classification on roads and highways, thereby helping in congestion analysis and traffic pattern characterization for better traffic management.

  2. Parking Management: This computer vision-based software can be implemented in parking lots for automatic detection of incoming and exiting vehicles, thus supporting automated ticketing processes and tracking the parking space occupancy.

  3. Vehicle Insurance: Insurance companies can use this model to identify and categorize vehicles for underwriting policies, claim settlements, and fraud detection activities.

  4. Retail Gas Stations: The model can be integrated into the POS systems of retail gas stations to track customer vehicle types, enabling the formulation of vehicle-class-specific promotional offers and strategies.

  5. Vehicle Manufacturing Industry: Automobile manufacturers can deploy this model at their manufacturing facilities to identify and classify manufactured vehicles for inventory management and quality control purposes.

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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{
                            als_batch2_dataset,
                            title = { als_bATCH2 Dataset },
                            type = { Open Source Dataset },
                            author = { Leela Kantheti },
                            howpublished = { \url{ https://universe.roboflow.com/leela-kantheti/als_batch2 } },
                            url = { https://universe.roboflow.com/leela-kantheti/als_batch2 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { apr },
                            note = { visited on 2024-11-23 },
                            }
                        
                    

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