Lin et al., 2022 - Google Patents
Interventional multi-instance learning with deconfounded instance-level predictionLin et al., 2022
View PDF- Document ID
- 2611981473705088824
- Author
- Lin T
- Xu H
- Yang C
- Xu Y
- Publication year
- Publication venue
- Proceedings of the AAAI Conference on Artificial Intelligence
External Links
Snippet
When applying multi-instance learning (MIL) to make predictions for bags of instances, the prediction accuracy of an instance often depends on not only the instance itself but also its context in the corresponding bag. From the viewpoint of causal inference, such bag …
- 230000001364 causal effect 0 abstract description 32
Classifications
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- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6256—Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
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- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
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- G06K9/52—Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
- G06K9/527—Scale-space domain transformation, e.g. with wavelet analysis
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- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
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