IsaacRodgz/ConcatBERT

Baseline model for multimodal classification based on images and text. Text representation obtained from pretrained BERT base model and image representation obtained from VGG16 pretrained model.

29
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Experimental

This tool helps researchers and data scientists classify content that combines both images and text, such as social media posts, product reviews, or movie data. It takes in an image and its accompanying text, processes them using established AI models, and then outputs a classification or prediction, helping to automate tasks like content moderation or sentiment analysis. The primary users are data scientists and researchers working with mixed media datasets.

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Use this if you need to classify items where both an image and related text are crucial for making an accurate prediction, and you want a straightforward, effective baseline model.

Not ideal if your classification task relies solely on text or solely on images, or if you require extremely lightweight models for deployment on resource-constrained devices.

multimodal-classification content-moderation sentiment-analysis social-media-analysis media-categorization
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 13 / 25

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Last pushed

Aug 26, 2022

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