PaleoNeutrinosCLAHE Object Detection Dataset and Pre-Trained Model by PaleoNeutrinos

Images

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Explore Dataset

Here are a few use cases for this project:

Art Authentication: Utilizing the PaleoNeutrinosCLAHE computer vision model to analyze and identify potential artists and artistic styles, which can help art historians and experts determine the authenticity and originality of a particular piece of art.
Art Restoration and Preservation: Using the model to identify and analyze the specific artistic techniques, materials, and styles from various art classes, assisting conservators in restoring and preserving artwork in a manner consistent with the original artist's intentions.
Digital Art Archive and Search Engine: The PaleoNeutrinosCLAHE model can be applied in creating an extensive digital archive of various art classes, enabling art enthusiasts, researchers, and students the ability to easily search, locate and study artworks based on particular styles, styles, or techniques.
Art Education and Curation: Incorporating the model in art education and curation, allowing students and curators to better understand and identify artistic styles, techniques, and innovations. The model can also be used to create virtual guided tours of art galleries, museums, and exhibitions.
Trend Analysis and Creative Inspiration: Using the PaleoNeutrinosCLAHE model to analyze and determine the evolution of various art classes and styles over time, providing artists and designers with a rich source of inspiration and insight into emerging and historical trends in the art world.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            paleoneutrinosclahe_dataset,
                            title = { PaleoNeutrinosCLAHE Dataset },
                            type = { Open Source Dataset },
                            author = { PaleoNeutrinos },
                            howpublished = { \url{ https://universe.roboflow.com/paleoneutrinos/paleoneutrinosclahe } },
                            url = { https://universe.roboflow.com/paleoneutrinos/paleoneutrinosclahe },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-05-05 },
                            }