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Anomaly Detection

104 papers with code ยท Methodology

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CBOWRA: A Representation Learning Approach for Medication Anomaly Detection

20 Aug 2019

Electronic health record is an important source for clinical researches and applications, and errors inevitably occur in the data, which could lead to severe damages to both patients and hospital services.

ANOMALY DETECTION REPRESENTATION LEARNING

Detection of Shilling Attack Based on T-distribution on the Dynamic Time Intervals in Recommendation Systems

18 Aug 2019

First of all, based on the characteristics of shilling attack quickness (Attackers inject a large number of fake profiles in a short period in order to save costs), we use dynamic time interval method to divide the rating history of item into multiple time windows.

ANOMALY DETECTION RECOMMENDATION SYSTEMS

Anomaly Detection in Video Sequence with Appearance-Motion Correspondence

17 Aug 2019

The training stage is performed using only videos of normal events and the model is then capable to estimate frame-level scores for an unknown input.

ANOMALY DETECTION IN SURVEILLANCE VIDEOS

Hybrid Deep Network for Anomaly Detection

17 Aug 2019

In this paper, we propose a deep convolutional neural network (CNN) for anomaly detection in surveillance videos.

ANOMALY DETECTION IN SURVEILLANCE VIDEOS

GODS: Generalized One-class Discriminative Subspaces for Anomaly Detection

16 Aug 2019

One-class learning is the classic problem of fitting a model to data for which annotations are available only for a single class.

ANOMALY DETECTION

Detecting abnormalities in resting-state dynamics: An unsupervised learning approach

16 Aug 2019

Resting-state functional MRI (rs-fMRI) is a rich imaging modality that captures spontaneous brain activity patterns, revealing clues about the connectomic organization of the human brain.

ANOMALY DETECTION

Detecting semantic anomalies

13 Aug 2019

We critically appraise the recent interest in out-of-distribution (OOD) detection, questioning the practical relevance of existing benchmarks.

ANOMALY DETECTION MULTI-TASK LEARNING OBJECT RECOGNITION

Anomaly Detection in High Dimensional Data

12 Aug 2019

The HDoutliers algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation.

ANOMALY DETECTION FEATURE ENGINEERING

SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks

11 Aug 2019

SpecAE leverages Laplacian sharpening to amplify the distances between representations of anomalies and the ones of the majority.

ANOMALY DETECTION DENSITY ESTIMATION

Deep Structured Cross-Modal Anomaly Detection

11 Aug 2019

To this end, we propose a novel deep structured anomaly detection framework to identify the cross-modal anomalies embedded in the data.

ANOMALY DETECTION