The 1st Workshop on​

Anomaly Detection in Unstructured Data (ADUD)

Anomaly detection is one of the machine/deep learning techniques with the largest number of practical applications; for example, predictive maintenance, cybersecurity and fraud detection, to name a few. On the other hand, unstructured data (mainly text, images and video) has become the predominant data in terms of size and number of applications compared to structured data. The union of both fields in what is called anomaly detection in unstructured data, is an area of active research in which advances are continually being made. This workshop is open to receive contributions
in this field both at theoretical level (algorithms) and at the practical level.

Chairman: Joan Vila-Francés ( and Antonio José Serrano-López (; researchers from the IDAL research group ( University of Valencia

Important dates

Please visit EANN / EAAAI 2023 important dates to be informed about the submission deadlines.

Submission instructions

Submission details can be found at AIAI / EANN / EAAAI conference submission page.

All papers should be submitted either in a doc/docx or in a pdf form and will be peer reviewed by at least 2 academic referees. Contributing authors must follow the EANN / EAAAI 2023’s paper format guidelines as far as the SPRINGER CCIS file format.

Papers will be peer reviewed by at least two (-2-) members of the workshop’s program committee.

Accepted papers will be published in the Proceedings of EANN / EAAAI VOLUME 2, under the SPRINGER CCIS Series.

Authors can submit their work for ADUD workshop through AIAI co-Organized submission site at

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