Subspace Clustering for Situation Assessment in Aquatic Drones: A Sensitivity Analysis for State-Model Improvement

Author:

Castellini Alberto1,Bicego Manuele1,Bloisi Domenico2,Blum Jason1,Masillo Francesco1,Peignier Sergio3,Farinelli Alessandro1

Affiliation:

1. Department of Computer Science, University of Verona, Verona, Italy;

2. Department of Mathematics, Computer Science, and Economics, University of Basilicata, Italy;

3. INSA-Lyon, Université de Lyon, France

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Information Systems,Software

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Background-Aware Classification Activation Map for Weakly Supervised Object Localization;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-12

2. Adversarial Data Augmentation for HMM-Based Anomaly Detection;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-12

3. Multivariate sensor signals collected by aquatic drones involved in water monitoring: A complete dataset;Data in Brief;2020-06

4. Time series segmentation for state-model generation of autonomous aquatic drones: A systematic framework;Engineering Applications of Artificial Intelligence;2020-04

5. Explaining the Influence of Prior Knowledge on POMCP Policies;Multi-Agent Systems and Agreement Technologies;2020

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