Robust Learning with Noisy Ship Trajectories by Adaptive Noise Rate Estimation
Ship trajectory classification is of great significance for shipping analysis and marine security governance. However, in order to cover up their illegal fishing or espionage activities, some illicit ships will forge the ship type information in the Automatic Identification System (AIS), and this la...
Main Authors: | Haoyu Yang, Mao Wang, Zhihao Chen, Kaiming Xiao, Xuan Li, Hongbin Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-07-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/23/15/6723 |
Similar Items
-
Learning Accurate Pseudo-Labels via Feature Similarity in the Presence of Label Noise
by: Peng Wang, et al.
Published: (2024-03-01) -
On the Suitability of Bagging-Based Ensembles with Borderline Label Noise
by: José A. Sáez, et al.
Published: (2022-06-01) -
An Adaptive and Robust Method for Oriented Oversampling With Spatial Information for Imbalanced Noisy Datasets
by: Yi Deng, et al.
Published: (2023-01-01) -
Agreement and Disagreement-Based Co-Learning with Dual Network for Hyperspectral Image Classification with Noisy Labels
by: Youqiang Zhang, et al.
Published: (2023-05-01) -
Label Noise Cleaning with an Adaptive Ensemble Method Based on Noise Detection Metric
by: Wei Feng, et al.
Published: (2020-11-01)