AOI-SSL combines small-domain self-supervised pre-training of vision transformers with in-context patch retrieval to reduce labeled data needs and enable fast adaptation for semiconductor wire-bond segmentation.
An image is worth 16x16 words: Transformers for image recognition at scale
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SinglePrompt achieves state-of-the-art results in task-free online continual learning by replacing prompt selection with a single prompt per attention block, cosine-based classifier logits, and masking unexposed classes.
citing papers explorer
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AOI-SSL: Self-Supervised Framework for Efficient Segmentation of Wire-bonded Semiconductors In Optical Inspection
AOI-SSL combines small-domain self-supervised pre-training of vision transformers with in-context patch retrieval to reduce labeled data needs and enable fast adaptation for semiconductor wire-bond segmentation.
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Is Prompt Selection Necessary for Task-Free Online Continual Learning?
SinglePrompt achieves state-of-the-art results in task-free online continual learning by replacing prompt selection with a single prompt per attention block, cosine-based classifier logits, and masking unexposed classes.