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Open Set Learning

Traditional supervised learning aims to train a classifier in the closed-set world, where training and test samples share the same label space. Open set learning (OSL) is a more challenging and realistic setting, where there exist test samples from the classes that are unseen during training. Open set recognition (OSR) is the sub-task of detecting test samples which do not come from the training.

Papers

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Showing 101–150 of 267 papers

TitleStatusHype
Deep Compact Polyhedral Conic Classifier for Open and Closed Set Recognition—0
Deep Learning and Open Set Malware Classification: A Survey—0
Deep Learning Approaches for Open Set Wireless Transmitter Authorization—0
Deep Open-Set Recognition for Silicon Wafer Production Monitoring—0
Deep Simplex Classifier for Maximizing the Margin in Both Euclidean and Angular Spaces—0
Denoising Autoencoders for Overgeneralization in Neural Networks—0
Dense outlier detection and open-set recognition based on training with noisy negative images—0
Detecting Unknown Attacks in IoT Environments: An Open Set Classifier for Enhanced Network Intrusion Detection—0
Distance-Based Background Class Regularization for Open-Set Recognition—0
Distribution Networks for Open Set Learning—0
Dummy Prototypical Networks for Few-Shot Open-Set Keyword Spotting—0
EdgeFM: Leveraging Foundation Model for Open-set Learning on the Edge—0
Effects of Common Regularization Techniques on Open-Set Recognition—0
Eight Years of Face Recognition Research: Reproducibility, Achievements and Open Issues—0
Empowering Knowledge Distillation via Open Set Recognition for Robust 3D Point Cloud Classification—0
Evaluating Uncertainty Calibration for Open-Set Recognition—0
Evaluation of Various Open-Set Medical Imaging Tasks with Deep Neural Networks—0
Face Detection on Surveillance Images—0
Familiarity-Based Open-Set Recognition Under Adversarial Attacks—0
Feature Decoupling in Self-supervised Representation Learning for Open Set Recognition—0
Feature-Space Semantic Invariance: Enhanced OOD Detection for Open-Set Domain Generalization—0
FedPD: Federated Open Set Recognition with Parameter Disentanglement—0
Few-shot Open-set Recognition Using Background as Unknowns—0
From Coarse to Fine-Grained Open-Set Recognition—0
FSOS-AMC: Few-Shot Open-Set Learning for Automatic Modulation Classification—0
Gallery-Aware Uncertainty Estimation For Open-Set Face Recognition—0
Generalizing Cross Entropy Loss with a Beta Proper Composite Loss: An Improved Loss Function for Open Set Recognition—0
Generative-Discriminative Feature Representations for Open-Set Recognition—0
G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition—0
Hierarchical Models: Intrinsic Separability in High Dimensions—0
Hybrid Models for Open Set Recognition—0
Hyperbolic Dual Feature Augmentation for Open-Environment—0
Open-Set Recognition Using Intra-Class Splitting—0
Open-set Recognition via Augmentation-based Similarity Learning—0
Open Set Recognition with Conditional Probabilistic Generative Models—0
Open-Set Recognition with Gaussian Mixture Variational Autoencoders—0
Open-Set Recognition with Gradient-Based Representations—0
Open-Set RF Fingerprinting via Improved Prototype Learning—0
Open-Set Video-based Facial Expression Recognition with Human Expression-sensitive Prompting—0
Open Set Wireless Transmitter Authorization: Deep Learning Approaches and Dataset Considerations—0
OpenSlot: Mixed Open-Set Recognition with Object-Centric Learning—0
Open-World Object Detection via Discriminative Class Prototype Learning—0
Orthogonal-Coding-Based Feature Generation for Transductive Open-Set Recognition via Dual-Space Consistent Sampling—0
Out-of-Distribution Data: An Acquaintance of Adversarial Examples -- A Survey—0
PartCom: Part Composition Learning for 3D Open-Set Recognition—0
PMAL: Open Set Recognition via Robust Prototype Mining—0
P-ODN: Prototype based Open Deep Network for Open Set Recognition—0
Polyhedral Conic Classifiers for Visual Object Detection and Classification—0
Towards Open-Set Myoelectric Gesture Recognition via Dual-Perspective Inconsistency Learning—0
Primate Face Identification in the Wild—0
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