SVT_Total_LCT Computer Vision Project
Updated 2 years ago
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downloadsHere are a few use cases for this project:
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Logo Identification: The SVT_Total_LCT model could be used to identify and classify different text types within logos. This could be beneficial for brand recognition, counterfeit detection, and trademark enforcement.
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Document Analysis: This model could be used for scanning and analyzing a variety of documents. By identifying and classifying different text classes, it could aid in information extraction, content management, and document categorization.
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Language Identification: If the variables represent different languages (e.g., "an," "ar," and "ntr"), the model could be used for identifying different languages present in an image, useful for translation services or for monitoring language usage in public signage.
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Accessibility Services: The model could be utilized to develop tools for the visually impaired. Turning written text (on signs, books, menus, etc.) into a format that could be read aloud would greatly enhance accessibility.
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Graffiti & Public Text Analysis: It may also be useful for city management and law enforcement agencies to identify, classify, and understand public texts such as graffiti, signs, or billboards for creating safer and clean public spaces.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
svt_total_lct_dataset,
title = { SVT_Total_LCT Dataset },
type = { Open Source Dataset },
author = { EssamHaider },
howpublished = { \url{ https://universe.roboflow.com/essamhaider/svt_total_lct } },
url = { https://universe.roboflow.com/essamhaider/svt_total_lct },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { sep },
note = { visited on 2024-12-31 },
}