HIGHLIGHTS
- who: Positive and colleagues from the (UNIVERSITY) have published the article: One-Class Remote Sensing Classification From Positive and Unlabeled Background Data, in the Journal: (JOURNAL)
- what: The authors propose a novel and learning with constraints (PBLC) algorithm to address this oneclass classification problem. To overcome these problems, the authors propose a new approach to learn a binary classifier using positive and unlabeled data focusing on the case-control scenario. In the following sections, the authors provide details about the algorithm, experiments, and discussions. Instead of arbitrarily selecting a subset of positive samples to estimate . . .
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