Buchumschlag

OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Pinon, Nicolas, Lartizien, Carole
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Machine Learning Artificial Intelligence Image and Video Processing
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Weakly supervised deep learning model with size constraint for prostate cancer detection in multiparametric MRI and generalization to unseen domains
von: Trombetta, Robin, et al.
Veröffentlicht: (2024)

Learning local and global prototypes with optimal transport for unsupervised anomaly detection and localization
von: Trombetta, Robin, et al.
Veröffentlicht: (2025)

GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models
von: Zotova, Daria, et al.
Veröffentlicht: (2025)

Federated brain tumor segmentation: an extensive benchmark
von: Manthe, Matthis, et al.
Veröffentlicht: (2024)

HOTSPOT-YOLO: A Lightweight Deep Learning Attention-Driven Model for Detecting Thermal Anomalies in Drone-Based Solar Photovoltaic Inspections
von: Dhimish, Mahmoud
Veröffentlicht: (2025)

Diffusion-Based Electrocardiography Noise Quantification via Anomaly Detection
von: Han, Tae-Seong, et al.
Veröffentlicht: (2025)

On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction
von: Han, Tianyu, et al.
Veröffentlicht: (2024)

From Load Tests to Live Streams: Graph Embedding-Based Anomaly Detection in Microservice Architectures
von: Madabhushi, Srinidhi, et al.
Veröffentlicht: (2026)

CogGen: Cognitive-Load-Informed Fully Unsupervised Deep Generative Modeling for Compressively Sampled MRI Reconstruction
von: Zhu, Qingyong, et al.
Veröffentlicht: (2026)

Electrocardiogram (ECG) Based Cardiac Arrhythmia Detection and Classification using Machine Learning Algorithms
von: Pokharel, Atit, et al.
Veröffentlicht: (2024)

Data-Efficient Psychiatric Disorder Detection via Self-supervised Learning on Frequency-enhanced Brain Networks
von: Liu, Mujie, et al.
Veröffentlicht: (2025)

Interpretable Neuropsychiatric Diagnosis via Concept-Guided Graph Neural Networks
von: Wang, Song, et al.
Veröffentlicht: (2025)

Subspace Implicit Neural Representations for Real-Time Cardiac Cine MR Imaging
von: Huang, Wenqi, et al.
Veröffentlicht: (2024)

Hybrid Efficient Unsupervised Anomaly Detection for Early Pandemic Case Identification
von: Ghajari, Ghazal, et al.
Veröffentlicht: (2024)

Pediatric Appendicitis Detection from Ultrasound Images
von: Hosseinabadi, Fatemeh, et al.
Veröffentlicht: (2025)

Anomaly Detection in Automated Fibre Placement: Learning with Data Limitations
von: Ghamisi, Assef, et al.
Veröffentlicht: (2023)

Out-of-Distribution Detection and Data Drift Monitoring using Statistical Process Control
von: Zamzmi, Ghada, et al.
Veröffentlicht: (2024)

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing
von: Ayers, Jacob Glenn, et al.
Veröffentlicht: (2025)

FQPDR: Federated Quantum Neural Network for Privacy-preserving Early Detection of Diabetic Retinopathy
von: De, Debashis, et al.
Veröffentlicht: (2026)

AI-Based Detection of Temporal Changes in MR-Linac Images Acquired During Routine Prostate Radiotherapy
von: Park, Seungbin, et al.
Veröffentlicht: (2026)

Physics-Guided Conditional Diffusion Networks for Microwave Image Reconstruction
von: Chehelgami, Shirin, et al.
Veröffentlicht: (2025)

Improving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach
von: Xi, Pei, et al.
Veröffentlicht: (2024)

Deep Active Learning for Lung Disease Severity Classification from Chest X-rays: Learning with Less Data in the Presence of Class Imbalance
von: Gabriel, Roy M., et al.
Veröffentlicht: (2025)

Machine Learning and Transformers for Thyroid Carcinoma Diagnosis: A Review
von: Habchi, Yassine, et al.
Veröffentlicht: (2024)

DeepHQ: Learned Hierarchical Quantizer for Progressive Deep Image Coding
von: Lee, Jooyoung, et al.
Veröffentlicht: (2024)

FSSC: Federated Learning of Transformer Neural Networks for Semantic Image Communication
von: Yan, Yuna, et al.
Veröffentlicht: (2024)

Enhancing Free-hand 3D Photoacoustic and Ultrasound Reconstruction using Deep Learning
von: Lee, SiYeoul, et al.
Veröffentlicht: (2025)

Ultra-Strong Gradient Diffusion MRI with Self-Supervised Learning for Prostate Cancer Characterization
von: Patil, Tanishq, et al.
Veröffentlicht: (2025)

LIBR+: Improving Intraoperative Liver Registration by Learning the Residual of Biomechanics-Based Deformable Registration
von: Wang, Dingrong, et al.
Veröffentlicht: (2024)

Deep Dive into MRI: Exploring Deep Learning Applications in 0.55T and 7T MRI
von: Alves, Ana Carolina, et al.
Veröffentlicht: (2024)

An Explainable Deep Learning-Based Method For Schizophrenia Diagnosis Using Generative Data-Augmentation
von: Saadatinia, Mehrshad, et al.
Veröffentlicht: (2023)

Reliable Explainability of Deep Learning Spatial-Spectral Classifiers for Improved Semantic Segmentation in Autonomous Driving
von: Gutiérrez-Zaballa, Jon, et al.
Veröffentlicht: (2025)

Smart Diagnosis and Early Intervention in PCOS: A Deep Learning Approach to Women's Reproductive Health
von: Abrar, Shayan, et al.
Veröffentlicht: (2026)

Towards Deep Learning Surrogate for the Forward Problem in Electrocardiology: A Scalable Alternative to Physics-Based Models
von: Ogbomo-Harmitt, Shaheim, et al.
Veröffentlicht: (2025)

How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning
von: Wang, Yuanyuan, et al.
Veröffentlicht: (2024)

Dynamic Semantic Compression for CNN Inference in Multi-access Edge Computing: A Graph Reinforcement Learning-based Autoencoder
von: Li, Nan, et al.
Veröffentlicht: (2024)

IceBench-S2S: A Benchmark of Deep Learning for Challenging Subseasonal-to-Seasonal Daily Arctic Sea Ice Forecasting in Deep Latent Space
von: Xu, Jingyi, et al.
Veröffentlicht: (2026)

HyPer-EP: Meta-Learning Hybrid Personalized Models for Cardiac Electrophysiology
von: Jiang, Xiajun, et al.
Veröffentlicht: (2024)

Research on Feature Extraction Data Processing System For MRI of Brain Diseases Based on Computer Deep Learning
von: Xiao, Lingxi, et al.
Veröffentlicht: (2024)

Physics-Informed Neural Networks vs. Physics Models for Non-Invasive Glucose Monitoring: A Comparative Study Under Noise-Stressed Synthetic Conditions
von: Gani, Riyaadh
Veröffentlicht: (2025)