Open Set Recognition for Automatic Target Classification With Rejection

被引：75

作者：

Scherreik, Matthew D. ^{[1
]}

Rigling, Brian D. ^{[1
]}

机构：

[1] Wright State Univ, Elect Engn, 3640 Colonel Glenn Highway, Dayton, OH 45435 USA

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2016年 / 52卷 / 02期

基金：

美国国家科学基金会;

关键词：

SUPPORT;

D O I：

10.1109/TAES.2015.150027

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

Training sets for supervised classification tasks are usually limited in scope and only contain examples of a few classes. In practice, classes that were not seen in training are given labels that are always incorrect. Open set recognition (OSR) algorithms address this issue by providing classifiers with a rejection option for unknown samples. In this work, we introduce a new OSR algorithm and compare its performance to other current approaches for open set image classification.

引用

页码：632 / 642

页数：11

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