Probabilistic SVM for open set automatic target recognition on high range resolution radar dataOpen Set ClassificationHigh Range Resolution (HRR) RadarSupport Vector Machine (SVM)Eigen TemplateThe Eigen-Template (ET) based closed-set feature extraction approach is extended to an open-set HRR-ATR ...
Open set recognition for automatic target classification with rejection Training sets for supervised classification tasks are usually limited in scope and only contain examples of a few classes. In practice, classes that were n... MD Scherreik,BD Rigling - 《IEEE Transactions on Aerospace & Electro...
Domain adaptation for visual recognition has undergone great progress in the past few years. Nevertheless, most existing methods work in the so-called closed-set scenario, assuming that the classes depicted by the target images are exactly the same as those of the source domain. In this paper,...
Due to the flexibility, survivability and long-distance transmission, shortwave communication has always been a reserved and development method in the field of wireless communication. Shortwave signal automatic recognition technology [1] is an important content of signal blind processing and an important ...
Unsupervised domain adaptation (UDA) has proven to be very effective in transferring knowledge obtained from a source domain with labeled data to a target domain with unlabeled data. Owing to the lack of labeled data in the target domain and the possible presence of unknown classes, open-set do...
In this paper, we propose a method for out-of-vocabulary (OOV) word detection and take a step toward open vocabulary automatic speech recognition. The prop... A Yazgan,M Saraclar - IEEE International Conference on Acoustics 被引量: 80发表: 2004年 Development, reliability, and validity of PR...
Face anti-spoofing is a critical component of face recognition technology. However, it suffers from poor generalizability for cross-scenario target domains due to the simultaneous presence of unseen domains and unknown attack types. In this paper, we first propose a challenging but practical problem ...
5.1. Open-Set Recognition In this section we apply the proposed methods to var- ious open-set recognition problems and present quantita- tive results on publicly available benchmarks. In open-set recognition scenarios, each input probe either has a match in the galler...
SAR Target Open-Set Recognition Based on Joint Training of Class-Specific Sub-Dictionary Learning IEEE Geosci Remote Sens Lett, 21 (2024), pp. 1-5, 10.1109/LGRS.2023.3342904 Google Scholar Qiu et al., 2022 K Qiu, W Song, P Wang Abnormal data detection for industrial processes using adversa...
Deep learning has already been proven to be an efficient data-driven technology for fault detection, owing to its remarkable advantages, such as automatic feature extraction and end-to-end process architecture [2]. When large-scale labeled data for supervised learning are available, the fault ...