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.
Please visit AIAI 2023 important dates to be informed about the submission deadlines.
Submission details can be found at AIAI 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 AIAI2023’s paper format guidelines as far as the IFIP AICT 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 AIAI VOLUME 2, under the Springer IFIP AICT Series.
You can submit you ADUD paper here http://www.easyacademia.org/aiai2023.