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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 151–200 of 267 papers

TitleStatusHype
Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning—0
Vocabulary-informed Extreme Value Learning—0
Zero-Knowledge Zero-Shot Learning for Novel Visual Category Discovery—0
An In-Depth Study on Open-Set Camera Model Identification—0
Zero-X: A Blockchain-Enabled Open-Set Federated Learning Framework for Zero-Day Attack Detection in IoV—0
Comparison of Embedded Spaces for Deep Learning Classification—0
Open Set Recognition for Random Forest—0
Advanced Vision Transformers and Open-Set Learning for Robust Mosquito Classification: A Novel Approach to Entomological Studies—0
Adversarial Robustness: Softmax versus Openmax—0
Alignment Based Matching Networks for One-Shot Classification and Open-Set Recognition—0
Alignment Based Mathching Networks for One-Shot Classification and Open-Set Recognition—0
All Beings Are Equal in Open Set Recognition—0
An Adaptable Deep Learning-Based Intrusion Detection System to Zero-Day Attacks—0
Analysis and Applications of Deep Learning with Finite Samples in Full Life-Cycle Intelligence of Nuclear Power Generation—0
An Empirical Exploration of Open-Set Recognition via Lightweight Statistical Pipelines—0
An Entropy-Awareness Meta-Learning Method for SAR Open-Set ATR—0
A novel network training approach for open set image recognition—0
Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?—0
A Survey on Open-Set Image Recognition—0
A Survey on Open Set Recognition—0
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning—0
Boosting Deep Open World Recognition by Clustering—0
Breaking with Fixed Set Pathology Recognition through Report-Guided Contrastive Training—0
C2AE: Class Conditioned Auto-Encoder for Open-set Recognition—0
Cascade Evidential Learning for Open-World Weakly-Supervised Temporal Action Localization—0
Cascading Unknown Detection with Known Classification for Open Set Recognition—0
Class Information Guided Reconstruction for Automatic Modulation Open-Set Recognition—0
Class-Specific Semantic Reconstruction for Open Set Recognition—0
Collective decision for open set recognition—0
Collective Decision of One-vs-Rest Networks for Open Set Recognition—0
Data-Driven Hierarchical Open Set Recognition—0
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
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