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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 151–175 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
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