We consider the problem of simultaneous sparse coding and anomaly detection in a collection of data vectors.
Abstract We consider the problem of simultaneous sparse coding and anomaly detection in a collection of data vectors. The majority of the data vectors are ...
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In this article, we present the use of sparse representation of signal and dictionary learning method for solving the problem of anomaly detection. The analyzed ...
Jul 12, 2014 · Sparse coding and anomaly detection are important tasks, with numerous signal processing applications. This paper presented a unified approach ...
In this paper, we propose a sparse coding based approach for anomaly detection. More specifically, a dictionary is learnt to encode regular patterns in terms of ...
We consider the problem of simultaneous sparse coding and anomaly detection in a collection of data vectors. The ma- jority of the data vectors are assumed to ...
This repo is the official open source of [A revisit of sparse coding based anomaly detection in stacked rnn framework, ICCV 2017].
A lightweight Fast Sparse Coding Network (FSCN) is proposed to tackle anomaly detection based on STFF, which can be implemented on mainstream deep learning ...
We propose a Temporally-coherent Sparse Coding (TSC) where we enforce similar neighbouring frames be encoded with similar reconstruction coefficients.
This paper presents an anomaly detection method that is based on a sparse coding inspired Deep Neural Networks (DNN). Specifically, in light of the success of ...