A user on r/MachineLearning is seeking advice on the best architectural approach for a binary classification task to detect the presence of text within images. They are considering using a fine-tuned PaddleOCR v6 detection backbone (LCNetv4) and are exploring different methods, such as global average pooling or a grid-based approach, while also considering the implications of having only yes/no labels instead of bounding boxes. AI
RANK_REASON This is a user query on a subreddit, not a formal announcement or research paper.
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