C2AE: Class Conditioned Auto-Encoder for Open-Set Recognition
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- Type
- preprint
- Published
- 2019-04-02
- Cited by
- 419
- References
- 52
- Access
- Open access
- OpenAlex
- https://openalex.org/W2935590460
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:91184609
Keywords
Class (philosophy), Set (abstract data type), Computer science, Artificial intelligence, Task (project management)
References
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- You Only Look Once: Unified, Real-Time Object Detection
- Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Deep Learning Face Attributes in the Wild
- Towards Open World Recognition
- Goodness-of-Fit Tests for the Generalized Pareto Distribution
- An Introduction to Trends in Extreme Weather and Climate Events: Observations, Socioeconomic Impacts, Terrestrial Ecological Impacts, and Model Projections*
- Probability Models for Open Set Recognition
- Residual Life Time at Great Age
- Statistical Inference Using Extreme Order Statistics
- Modeling biometric systems using the general pareto distribution (GPD)
- Computing Maximum Likelihood Estimates for the Generalized Pareto Distribution
- Toward Open Set Recognition
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition
- Nearest neighbors distance ratio open-set classifier
- Towards Open Set Deep Networks
- Reading Digits in Natural Images with Unsupervised Feature Learning
- Deep Multitask Learning for Railway Track Inspection
Cited by
- Human Action Recognition and Prediction: A Survey
- Recent Advances in Open Set Recognition: A Survey
- Deep Transfer Learning for Multiple Class Novelty Detection
- OCGAN: One-Class Novelty Detection Using GANs With Constrained Latent Representations
- Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning
- Hierarchical Models: Intrinsic Separability in High Dimensions
- Hybrid Models for Open Set Recognition
- Class Anchor Clustering: a Distance-based Loss for Training Open Set Classifiers
- One-vs-Rest Network-based Deep Probability Model for Open Set Recognition
- Motion-based representations for activity recognition
- Open-Set Recognition with Gaussian Mixture Variational Autoencoders
- Conditional Gaussian Distribution Learning for Open Set Recognition
- Generative-Discriminative Feature Representations for Open-Set Recognition
- Fully convolutional open set segmentation
- ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection
- Retracted on July 26, 2022: Open set recognition through unsupervised and class-distance learning
- Representative-Discriminative Learning for Open-set Land Cover Classification of Satellite Imagery
- Open Set Recognition with Conditional Probabilistic Generative Models
- Deep Learning Based Open Set Acoustic Scene Classification
- A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
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