{"total":20,"rows":[{"id":"2110.11334","title":"Generalized Out-of-Distribution Detection: A Survey","created":"2021-10-21","cited_by_count":802,"area":null},{"id":"2103.04257","title":"Student-Teacher Feature Pyramid Matching for Anomaly Detection","created":"2021-03-07","cited_by_count":146,"area":null},{"id":"2101.03064","title":"One-Class Classification: A Survey","created":"2021-01-08","cited_by_count":35,"area":null},{"id":"2111.15376","title":"Reconstruction Student with Attention for Student-Teacher Pyramid Matching","created":"2021-11-30","cited_by_count":20,"area":null},{"id":"2507.21160","title":"Handling Out-of-Distribution Data: A Survey","created":"2025-07-25","cited_by_count":14,"area":null},{"id":"2107.02067","title":"Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation","created":"2021-07-05","cited_by_count":10,"area":null},{"id":"2207.08210","title":"A Simple Test-Time Method for Out-of-Distribution Detection","created":"2022-07-17","cited_by_count":6,"area":null},{"id":"2502.12849","title":"Leveraging Intermediate Representations for Better Out-of-Distribution Detection","created":"2025-02-18","cited_by_count":5,"area":null},{"id":"2105.01924","title":"Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder","created":"2021-05-05","cited_by_count":4,"area":null},{"id":"2110.15108","title":"Multi-Class Anomaly Detection","created":"2021-10-28","cited_by_count":3,"area":null},{"id":"2201.06378","title":"Self-Supervised Anomaly Detection by Self-Distillation and Negative Sampling","created":"2022-01-17","cited_by_count":3,"area":null},{"id":"2204.04665","title":"Effective Out-of-Distribution Detection in Classifier Based on PEDCC-Loss","created":"2022-04-10","cited_by_count":3,"area":null},{"id":"2409.13138","title":"Learning to Compare Hardware Designs for High-Level Synthesis","created":"2024-09-20","cited_by_count":3,"area":null},{"id":"2212.06023","title":"Reconstructing Humpty Dumpty: Multi-feature Graph Autoencoder for Open Set Action Recognition","created":"2022-12-12","cited_by_count":2,"area":null},{"id":"2212.06130","title":"Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets","created":"2022-12-12","cited_by_count":1,"area":null},{"id":"2502.19922","title":"Incremental Learning with Repetition via Pseudo-Feature Projection","created":"2025-02-27","cited_by_count":1,"area":null},{"id":"2111.14343","title":"Anomaly-Aware Semantic Segmentation by Leveraging Synthetic-Unknown Data","created":"2021-11-29","cited_by_count":0,"area":null},{"id":"2402.18112","title":"Simple But Effective: Rethinking the Ability of Deep Learning in fNIRS to Exclude Abnormal Input","created":"2024-02-28","cited_by_count":0,"area":null},{"id":"2411.09986","title":"Unlocking Transfer Learning for Open-World Few-Shot Recognition","created":"2024-11-15","cited_by_count":0,"area":null},{"id":"2512.18219","title":"Unsupervised Anomaly Detection with an Enhanced Teacher for Student-Teacher Feature Pyramid Matching","created":"2025-12-20","cited_by_count":0,"area":null}],"next_cursor":null}