A Probabilistic Bag-to-Class Approach to Multiple-Instance Learning
Multi-instance (MI) learning is a branch of machine learning, where each object (bag) consists of multiple feature vectors (instances)—for example, an image consisting of multiple patches and their corresponding feature vectors. In MI classification, each bag in the training set has a class label, b...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-06-01
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| Series: | Data |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2306-5729/5/2/56 |