Imagens marcas mae Computer Vision Project

treino imagens

Updated a year ago

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Classes (12)
25
26
27
29
30
balance
claybom
concorencia
deline
lektrek
miss daisy
pessoa

Metrics

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Description

Here are a few use cases for this project:

  1. Product Consumption Tracking: The model can be used in retail environments (like supermarkets) to monitor the consuming of different products (classes 27, 30, 25, etc.) and their major competitors (concorencia) to understand consumer preferences and predict product trends.

  2. Advertisement Effectiveness Metrics: In advertising and marketing efforts, the model can detect and analyze the visibility of various products (such as balance, deline, claybom, etc.) in different forms of media, providing valuable metrics for assessing advertisement reach and effectiveness.

  3. Consumer Research: The model can be utilized in consumer research studies to comprehend consumer behavior in choice of brands (like miss daisy, lektrek, etc.), especially in marketplaces, to provide insights for overall brand performance.

  4. Pet Food Consumption: Using the example image of a dog lying on its back in the grass, the model could have potential applications in monitoring and analyzing pet food consumption and brand preferences (e.g., claybom), providing valuable insights for pet food manufacturers and suppliers.

  5. Public Personality Identification: With the inclusion of 'pessoa' (person in Portuguese) as an identified class, it indicates potential use in public personality recognition in varied media sources which can be useful in pop culture analytics, security measures, or social media monitoring.

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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{
                            imagens-marcas-mae_dataset,
                            title = { Imagens marcas mae Dataset },
                            type = { Open Source Dataset },
                            author = { treino imagens },
                            howpublished = { \url{ https://universe.roboflow.com/treino-imagens/imagens-marcas-mae } },
                            url = { https://universe.roboflow.com/treino-imagens/imagens-marcas-mae },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { oct },
                            note = { visited on 2024-12-26 },
                            }
                        
                    

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