Image de couverture de livre

Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspective

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Cai, Yu, Chen, Hao, Cheng, Kwang-Ting
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Computer Vision and Pattern Recognition
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Revisiting Deep Ensemble Uncertainty for Enhanced Medical Anomaly Detection
par: Gu, Yi, et autres
Publié: (2024)

Bayesian Autoencoder for Medical Anomaly Detection: Uncertainty-Aware Approach for Brain 2 MRI Analysis
par: Roy, Dip
Publié: (2025)

Self-Supervised Training with Autoencoders for Visual Anomaly Detection
par: Bauer, Alexander, et autres
Publié: (2022)

Rethinking Decoupled Knowledge Distillation: A Predictive Distribution Perspective
par: Zheng, Bowen, et autres
Publié: (2025)

Quantization Variation: A New Perspective on Training Transformers with Low-Bit Precision
par: Huang, Xijie, et autres
Publié: (2023)

Exploiting Autoencoder's Weakness to Generate Pseudo Anomalies
par: Astrid, Marcella, et autres
Publié: (2024)

Rethinking Continual Anomaly Detection on the Edge: Benchmarking Under Realistic Industrial Conditions
par: Weatherly, Chad, et autres
Publié: (2026)

VAN-AD: Visual Masked Autoencoder with Normalizing Flow For Time Series Anomaly Detection
par: Chen, PengYu, et autres
Publié: (2026)

Rethinking Boundary Detection in Deep Learning-Based Medical Image Segmentation
par: Lin, Yi, et autres
Publié: (2025)

Sparse Autoencoders for Interpretable Medical Image Representation Learning
par: Wesp, Philipp, et autres
Publié: (2026)

Sampling Foundational Transformer: A Theoretical Perspective
par: Nguyen, Viet Anh, et autres
Publié: (2024)

Counterfactual Explanations for Medical Image Classification and Regression using Diffusion Autoencoder
par: Atad, Matan, et autres
Publié: (2024)

Research on Anomaly Detection Methods Based on Diffusion Models
par: Chen, Yi
Publié: (2025)

Object Detection for Medical Image Analysis: Insights from the RT-DETR Model
par: He, Weijie, et autres
Publié: (2025)

Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior
par: Liu, Yidan, et autres
Publié: (2024)

On the Problem of Consistent Anomalies in Zero-Shot Anomaly Detection
par: Le-Gia, Tai
Publié: (2025)

Multimodal Variational Autoencoder for Low-cost Cardiac Hemodynamics Instability Detection
par: Suvon, Mohammod N. I., et autres
Publié: (2024)

Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective
par: Wen, Qishuai, et autres
Publié: (2024)

Anomaly Detection in Medical Imaging -- A Mini Review
par: Tschuchnig, Maximilian E., et autres
Publié: (2021)

Is Hyperbolic Space All You Need for Medical Anomaly Detection?
par: Gonzalez-Jimenez, Alvaro, et autres
Publié: (2025)

FiLo: Zero-Shot Anomaly Detection by Fine-Grained Description and High-Quality Localization
par: Gu, Zhaopeng, et autres
Publié: (2024)

Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective
par: Lu, Aojun, et autres
Publié: (2025)

Set Features for Anomaly Detection
par: Cohen, Niv, et autres
Publié: (2023)

ResAD: A Simple Framework for Class Generalizable Anomaly Detection
par: Yao, Xincheng, et autres
Publié: (2024)

Rethinking the Bias of Foundation Model under Long-tailed Distribution
par: Chen, Jiahao, et autres
Publié: (2025)

The Boundaries of Fair AI in Medical Image Prognosis: A Causal Perspective
par: Pham, Thai-Hoang, et autres
Publié: (2025)

Adversarially Robust Industrial Anomaly Detection Through Diffusion Model
par: Cao, Yuanpu, et autres
Publié: (2024)

Robust Spectral Anomaly Detection in EELS Spectral Images via Three Dimensional Convolutional Variational Autoencoders
par: Sultanov, Seyfal, et autres
Publié: (2024)

SARMAE: Masked Autoencoder for SAR Representation Learning
par: Liu, Danxu, et autres
Publié: (2025)

Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline
par: Al-lahham, Anas, et autres
Publié: (2024)

MedIAnomaly: A comparative study of anomaly detection in medical images
par: Cai, Yu, et autres
Publié: (2024)

Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt
par: Liu, Jiaqi, et autres
Publié: (2024)

MedSapiens: Taking a Pose to Rethink Medical Imaging Landmark Detection
par: Elbatel, Marawan, et autres
Publié: (2025)

Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection
par: Orglmeister, Conrad, et autres
Publié: (2025)

Towards Universal Unsupervised Anomaly Detection in Medical Imaging
par: Bercea, Cosmin I., et autres
Publié: (2024)

Diffusion Models with Implicit Guidance for Medical Anomaly Detection
par: Bercea, Cosmin I., et autres
Publié: (2024)

Hyperspectral Anomaly Detection Fused Unified Nonconvex Tensor Ring Factors Regularization
par: Qin, Wenjin, et autres
Publié: (2025)

Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning
par: Bugarin, Nikola, et autres
Publié: (2024)

Rethinking the Unpretentious U-net for Medical Ultrasound Image Segmentation
par: Chen, Gongping, et autres
Publié: (2022)

Rethinking Comprehensive Benchmark for Chart Understanding: A Perspective from Scientific Literature
par: Shen, Lingdong, et autres
Publié: (2024)