| 개발자: | Funmula Corp Limited (2) | ||
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| App Store | |||
기술
A Fresh Breakthrough
BIRSE is built upon generative tools, establishing a zero-sample learning model that combines text and images. This innovative image search system, much like renowned Vision Language Models (LLMs), possesses "image comprehension" capabilities. It goes beyond mere appearances and colors, allowing it to identify images with shared meaning. This includes characteristics such as the texture and style of an item, solving the complexity of expressing certain attributes in words that standard image searches cannot analyze.
Application Scenarios
In the past, using the BigGo search engine required inputting keywords to query and compare products. While this approach suits items with explicit specifications, like computer components and electronics, it is less effective for fashion, furniture, or objects with various styles and materials that are difficult to describe textually.
Product Orientation
Another challenge is that search results, especially for fashion-related content, often lead to image databases and influencer outfit photos. Finding direct purchase options on shopping platforms used to be limited or even impossible. Before the introduction of BIRSE, other image search systems offered similar functionality, but their search scale and accuracy were not particularly outstanding. With BigGo's substantial parameter models and a database of 500 million local products, we aim to enhance this application's capabilities and help users quickly locate their desired products.
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