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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 201–250 of 267 papers

TitleStatusHype
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
ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection—0
Individual common dolphin identification via metric embedding learning—0
Informed Decision-Making through Advancements in Open Set Recognition and Unknown Sample Detection—0
Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation—0
Open-set learning with augmented categories by exploiting unlabelled data—0
Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders—0
Knowledge is Never Enough: Towards Web Aided Deep Open World Recognition—0
Know Yourself Better: Diverse Discriminative Feature Learning Improves Open Set Recognition—0
Latent Cognizance: What Machine Really Learns—0
Latent Space Energy-based Model for Fine-grained Open Set Recognition—0
Reconstruction guided Meta-learning for Few Shot Open Set Recognition—0
Learning for Transductive Threshold Calibration in Open-World Recognition—0
Learning Large Margin Sparse Embeddings for Open Set Medical Diagnosis—0
Learning the Compositional Spaces for Generalized Zero-shot Learning—0
On the link between generative semi-supervised learning and generative open-set recognition—0
LORD: Leveraging Open-Set Recognition with Unknown Data—0
M2IOSR: Maximal Mutual Information Open Set Recognition—0
Malware families discovery via Open-Set Recognition on Android manifest permissions—0
Managing the unknown: a survey on Open Set Recognition and tangential areas—0
MDENet: Multi-modal Dual-embedding Networks for Malware Open-set Recognition—0
Measuring Human Perception to Improve Open Set Recognition—0
MENTOR: Human Perception-Guided Pretraining for Increased Generalization—0
MetaMax: Improved Open-Set Deep Neural Networks via Weibull Calibration—0
More Information Supervised Probabilistic Deep Face Embedding Learning—0
Rectifying Open-set Object Detection: A Taxonomy, Practical Applications, and Proper Evaluation—0
One-vs-Rest Network-based Deep Probability Model for Open Set Recognition—0
OOD Augmentation May Be at Odds with Open-Set Recognition—0
OpenAPMax: Abnormal Patterns-based Model for Real-World Alzheimer's Disease Diagnosis—0
OpenClinicalAI: An Open and Dynamic Model for Alzheimer's Disease Diagnosis—0
openFEAT: Improving Speaker Identification by Open-set Few-shot Embedding Adaptation with Transformer—0
Open Long-Tailed Recognition in a Dynamic World—0
OpenNDD: Open Set Recognition for Neurodevelopmental Disorders Detection—0
Open-Set Facial Expression Recognition—0
Open Set Learning with Counterfactual Images—0
Open Set Medical Diagnosis—0
Open-Set Object Recognition Using Mechanical Properties During Interaction—0
Open-Set Plankton Recognition—0
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