MLF-SC: Incorporating multi-layer features to sparse coding for anomaly detection

1 code implementation • 9 Apr 2021 • Ryuji Imamura, Kohei Azuma, Atsushi Hanamoto, Atsunori Kanemura

The proposed method, multi-layer feature sparse coding (MLF-SC), employs a neural network for feature extraction, and feature maps from intermediate layers of the network are given to sparse coding, whereas the standard sparse-coding-based anomaly detection method directly works on given images.

Anomaly Detection

Coordination Structure Analysis using Dual Decomposition

no code implementations • EACL 2012 • Atsushi Hanamoto, Takuya Matsuzaki, Jun{'}ichi Tsujii