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Open Set Learning
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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.
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Disentangled representations of microscopy images
SASep: Saliency-Aware Structured Separation of Geometry and Feature for Open Set Learning on Point Clouds
Hyperbolic Dual Feature Augmentation for Open-Environment
Open-Set Semi-Supervised Learning for Long-Tailed Medical Datasets
Malware families discovery via Open-Set Recognition on Android manifest permissions
Structure-based Anomaly Detection and Clustering
Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation
Synthetic Non-stationary Data Streams for Recognition of the Unknown
BackMix: Regularizing Open Set Recognition by Removing Underlying Fore-Background Priors
Open-Set Plankton Recognition
SphOR: A Representation Learning Perspective on Open-set Recognition for Identifying Unknown Classes in Deep Learning Models
Open-Set Recognition of Novel Species in Biodiversity Monitoring
G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition
A Survey of Text Classification Under Class Distribution Shift
Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data
Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain Generalization
Robustness-enhanced Myoelectric Control with GAN-based Open-set Recognition
COOOL: Challenge Of Out-Of-Label A Novel Benchmark for Autonomous Driving
Unlocking Transfer Learning for Open-World Few-Shot Recognition
Feature-Space Semantic Invariance: Enhanced OOD Detection for Open-Set Domain Generalization
Electromagnetic Scattering Kernel Guided Reciprocal Point Learning for SAR Open-Set Recognition
Deep Learning for Leopard Individual Identification: An Adaptive Angular Margin Approach
Data-Driven Hierarchical Open Set Recognition
LEGO-Learn: Label-Efficient Graph Open-Set Learning
Open World Object Detection: A Survey
FSOS-AMC: Few-Shot Open-Set Learning for Automatic Modulation Classification
Solution for OOD-CV Workshop SSB Challenge 2024 (Open-Set Recognition Track)
Effects of Common Regularization Techniques on Open-Set Recognition
Dissecting Out-of-Distribution Detection and Open-Set Recognition: A Critical Analysis of Methods and Benchmarks
Gallery-Aware Uncertainty Estimation For Open-Set Face Recognition
Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set Recognition
Advanced Vision Transformers and Open-Set Learning for Robust Mosquito Classification: A Novel Approach to Entomological Studies
EOL: Transductive Few-Shot Open-Set Recognition by Enhancing Outlier Logits
Comparison of Embedded Spaces for Deep Learning Classification
Open Set Recognition for Random Forest
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