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Graph based Label Enhancement for Multi-instance Multi-label learning. (arXiv:2304.10705v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Multi-instance multi-label (MIML) learning is widely applicated in numerous
domains, such as the image classification where one image contains multiple
instances correlated with multiple logic labels simultaneously. The related
labels in existing MIML are all assumed as logical labels with equal
significance. However, in practical applications in MIML, significance of each
label for multiple instances per bag (such as an image) is significant
different. Ignoring labeling significance will greatly lose the semantic
information of the object, so that MIML is …
applications arxiv bag classification graph image information instances labeling labels logic multiple performance practical semantic significance