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Open Set Learning

10 papers with code · Miscellaneous

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Large-Scale Long-Tailed Recognition in an Open World

CVPR 2019 zhmiao/OpenLongTailRecognition-OLTR

We define Open Long-Tailed Recognition (OLTR) as learning from such naturally distributed data and optimizing the classification accuracy over a balanced test set which include head, tail, and open classes.

FEW-SHOT LEARNING OPEN SET LEARNING

Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

ICLR 2020 MrtnMndt/OCDVAE_ContinualLearning

We introduce a probabilistic approach to unify deep continual learning with open set recognition, based on variational Bayesian inference.

AUDIO CLASSIFICATION BAYESIAN INFERENCE CONTINUAL LEARNING OPEN SET LEARNING

Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?

26 Aug 2019MrtnMndt/Deep_Openset_Recognition_through_Uncertainty

We present an analysis of predictive uncertainty based out-of-distribution detection for different approaches to estimate various models' epistemic uncertainty and contrast it with extreme value theory based open set recognition.

OPEN SET LEARNING OUT-OF-DISTRIBUTION DETECTION

Conditional Gaussian Distribution Learning for Open Set Recognition

19 Mar 2020BraveGump/CGDL-for-Open-Set-Recognition

A typical challenge is that unknown samples may be fed into the system during the testing phase and traditional deep neural networks will wrongly recognize the unknown sample as one of the known classes.

OPEN SET LEARNING

Sparse Representation-based Open Set Recognition

6 May 2017hezhangsprinter/SROSR

We propose a generalized Sparse Representation- based Classification (SRC) algorithm for open set recognition where not all classes presented during testing are known during training.

OBJECT CLASSIFICATION OPEN SET LEARNING SPARSE REPRESENTATION-BASED CLASSIFICATION

AP18-OLR Challenge: Three Tasks and Their Baselines

2 Jun 2018Rithmax/Sub-band-Envelope-Features-Using-Frequency-Domain-Linear-Prediction

The third oriental language recognition (OLR) challenge AP18-OLR is introduced in this paper, including the data profile, the tasks and the evaluation principles.

OPEN SET LEARNING

Specialized Support Vector Machines for Open-set Recognition

13 Jun 2016pedrormjunior/ssvm-results

In the open-set scenario, however, a test sample can belong to none of the known classes and the classifier must properly reject it by classifying it as unknown.

OPEN SET LEARNING

Class Anchor Clustering: a Distance-based Loss for Training Open Set Classifiers

6 Apr 2020dimitymiller/cac-openset

Existing open set classifiers distinguish between known and unknown inputs by measuring distance in a network's logit space, assuming that known inputs cluster closer to the training data than unknown inputs.

OPEN SET LEARNING

Individual common dolphin identification via metric embedding learning

9 Jan 2019omallo/kaggle-whale

Photo-identification (photo-id) of dolphin individuals is a commonly used technique in ecological sciences to monitor state and health of individuals, as well as to study the social structure and distribution of a population.

OPEN SET LEARNING