A Brief Survey into the Field of Automatic Image Dataset Generation through Web Scraping and Query Expansion
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High-quality image datasets are in high demand for various applications. With many online sources providingmanually collected datasets, a persisting challenge is to fully automate the dataset collection process. In thisstudy, we surveyed an automatic image dataset generation field through analyzing a collection of existingstudies. Moreover, we examined fields that are closely related to automated dataset generation, such as queryexpansion, web scraping, and dataset quality. We assess how both noise and regional search engine differencescan be addressed using an automated search query expansion focused on hypernyms, allowing for user-specificmanual query expansion. Combining these aspects provides an outline of how a modern web scraping applicationcan produce large-scale image datasets.
Abstract
High-quality image datasets are in high demand for various applications. With many online sources providingmanually collected datasets, a persisting challenge is to fully automate the dataset collection process. In thisstudy, we surveyed an automatic image dataset generation field through analyzing a collection of existingstudies. Moreover, we examined fields that are closely related to automated dataset generation, such as queryexpansion, web scraping, and dataset quality. We assess how both noise and regional search engine differencescan be addressed using an automated search query expansion focused on hypernyms, allowing for user-specificmanual query expansion. Combining these aspects provides an outline of how a modern web scraping applicationcan produce large-scale image datasets.
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