Anomaly and Novelty detection for Satellite and Drone systems (ANSD'23)

0Citations
Citations of this article
27Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In recent times, there has been a notable surge in the amount of vision and sensing/time-series data obtained from drones and satellites. This data can be utilized in various fields, such as precision agriculture, disaster management, environmental monitoring, and others. However, the analysis of such data poses significant challenges due to its complexity, heterogeneity, and scale. Furthermore, it is critical to identify anomalies and maintain/monitor the health of drones and satellite systems to enable the aforementioned applications and sciences. This workshop presents an excellent opportunity to explore solutions that specifically target the detection of anomalies and novel occurrences in drones and satellite systems and their data. For more information, visit our website at https://sites.google.com/view/ansd23.

Cite

CITATION STYLE

APA

Tariq, S., Woo, S., Chung, D., & Shin, Y. (2023). Anomaly and Novelty detection for Satellite and Drone systems (ANSD’23). In International Conference on Information and Knowledge Management, Proceedings (pp. 5294–5295). Association for Computing Machinery. https://doi.org/10.1145/3583780.3615306

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free