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Anomaly Detection, Anomaly Segmentation, Novelty Detection, Out-of-Distribution Detection

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Latest papers without code

Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning

5 May 2021

On the MIMIC-III and Henan-Renmin EHR datasets, we report a detection accuracy of 77% against the Longitudinal Adversarial Attack.

ADVERSARIAL ATTACK ANOMALY DETECTION DECISION MAKING

An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs

4 May 2021

To the best of our knowledge, this is a first attempt to comparatively analyze the different evaluation frameworks used in the existing deep change detection methods.

ACTION RECOGNITION ANOMALY DETECTION OBJECT TRACKING

Unsupervised Anomaly Detection in MR Images using Multi-Contrast Information

2 May 2021

The feature is collaboratively used with another feature that is the low-dimensional representation of multi-contrast images.

DENSITY ESTIMATION UNSUPERVISED ANOMALY DETECTION

DRAM Failure Prediction in AIOps: Empirical Evaluation, Challenges and Opportunities

30 Apr 2021

DRAM failure prediction is a vital task in AIOps, which is crucial to maintain the reliability and sustainable service of large-scale data centers.

MULTI-CLASS CLASSIFICATION UNSUPERVISED ANOMALY DETECTION

Anomaly Detection with Prototype-Guided Discriminative Latent Embeddings

30 Apr 2021

Recent efforts towards video anomaly detection try to learn a deep autoencoder to describe normal event patterns with small reconstruction errors.

ANOMALY DETECTION OPTICAL FLOW ESTIMATION

Cleaning Label Noise with Clusters for Minimally Supervised Anomaly Detection

30 Apr 2021

Learning to detect real-world anomalous events using video-level annotations is a difficult task mainly because of the noise present in labels.

ANOMALY DETECTION

Discriminative-Generative Dual Memory Video Anomaly Detection

29 Apr 2021

In this paper, we propose a DiscRiminative-gEnerative duAl Memory (DREAM) anomaly detection model to take advantage of a few anomalies and solve data imbalance.

ANOMALY DETECTION

PANDA : Perceptually Aware Neural Detection of Anomalies

28 Apr 2021

Semi-supervised methods of anomaly detection have seen substantial advancement in recent years.

ANOMALY DETECTION DEFECT DETECTION

Inpainting Transformer for Anomaly Detection

28 Apr 2021

Anomaly detection in computer vision is the task of identifying images which deviate from a set of normal images.

ANOMALY DETECTION

Image Synthesis as a Pretext for Unsupervised Histopathological Diagnosis

28 Apr 2021

Anomaly detection in visual data refers to the problem of differentiating abnormal appearances from normal cases.

FACE GENERATION UNSUPERVISED ANOMALY DETECTION