{"total":20,"rows":[{"id":"2310.18961","title":"AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection","created":"2023-10-29","cited_by_count":271,"area":null},{"id":"2403.06495","title":"Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Prompts","created":"2024-03-11","cited_by_count":89,"area":null},{"id":"2405.14529","title":"AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2","created":"2024-05-23","cited_by_count":53,"area":null},{"id":"2410.00320","title":"PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection","created":"2024-10-01","cited_by_count":29,"area":null},{"id":"2412.03342","title":"UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection","created":"2024-12-04","cited_by_count":28,"area":null},{"id":"2404.04518","title":"MedIAnomaly: A comparative study of anomaly detection in medical images","created":"2024-04-06","cited_by_count":26,"area":null},{"id":"2601.10880","title":"Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation","created":"2026-01-15","cited_by_count":25,"area":null},{"id":"2308.06748","title":"Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch Retrieval","created":"2023-08-13","cited_by_count":22,"area":null},{"id":"2407.08813","title":"FairDomain: Achieving Fairness in Cross-Domain Medical Image Segmentation and Classification","created":"2024-07-11","cited_by_count":19,"area":null},{"id":"2409.14676","title":"TransUKAN:Computing-Efficient Hybrid KAN-Transformer for Enhanced Medical Image Segmentation","created":"2024-09-23","cited_by_count":6,"area":null},{"id":"2502.17132","title":"Applications of Large Models in Medicine","created":"2025-02-24","cited_by_count":6,"area":null},{"id":"2311.02189","title":"FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling","created":"2023-11-03","cited_by_count":5,"area":null},{"id":"2401.11734","title":"Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Survey","created":"2024-01-22","cited_by_count":5,"area":null},{"id":"2509.10282","title":"MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection","created":"2025-09-12","cited_by_count":2,"area":null},{"id":"2509.03277","title":"PointAD+: Learning Hierarchical Representations for Zero-shot 3D Anomaly Detection","created":"2025-09-03","cited_by_count":1,"area":null},{"id":"2603.19608","title":"FB-CLIP: Fine-Grained Zero-Shot Anomaly Detection with Foreground-Background Disentanglement","created":"2026-03-20","cited_by_count":1,"area":null},{"id":"2211.12565","title":"A Novel Center-based Deep Contrastive Metric Learning Method for the Detection of Polymicrogyria in Pediatric Brain MRI","created":"2022-11-22","cited_by_count":0,"area":null},{"id":"2311.14506","title":"Multi-Class Anomaly Detection based on Regularized Discriminative Coupled hypersphere-based Feature Adaptation","created":"2023-11-24","cited_by_count":0,"area":null},{"id":"2312.12599","title":"Unsupervised Segmentation of Colonoscopy Images","created":"2023-12-19","cited_by_count":0,"area":null},{"id":"2510.13643","title":"Adversarially Robust Few-Shot Anomaly Detection with Vision Foundation Models","created":"2025-10-15","cited_by_count":0,"area":null}],"next_cursor":null}