TY  - GEN 
AU  - Canizo, Mikel
AU  - Triguero Velázquez, Isaac
AU  - Conde, Angel
AU  - Onieva, Enrique
PY  - 2019
SN  - 0925-2312
SN  - 1872-8286
UR  - https://hdl.handle.net/10481/109577
AB  - Detecting anomalies in time series data is becoming mainstream in a wide variety of industrial applications in which sensors monitor expensive machinery. The complexity of this task increases when multiple heterogeneous sensors provide information of...
LA  - eng
PB  - Elsevier
KW  - Deep Learning
KW  - Anomaly detection
KW  - Convolutional neural networks
TI  - Multi-Head CNN-RNN for Multi-Time Series Anomaly Detection: An industrial case study
DO  - 10.1016/j.neucom.2019.07.034
ER  -