Intelligent ship monitoring technology, driven by its exceptional data fitting ability, has emerged as a crucial component within the field of intelligent maritime perception. However, existing deep learning-based ship monitoring studies primarily focus on minimizing the discrepancy between predicted and true labels during model training. This approach, unfortunately, restricts the model to learning only from labeled ship samp...

Ship detection in the maritime domain awareness field has seen a significant shift towards deep-learning-based techniques as the mainstream approach. However, most existing deep-learning-based ship detection models adopt a random sampling strategy for training data, neglecting the complexity differences among samples and the learning progress of the model, which hinders training efficiency, robustness, and generalization abili...

Vessel monitoring technology involves the application of remote sensing technologies to detect and identify vessels in various environments, which is critical for monitoring vessel traffic, identifying potential threats, and facilitating maritime safety and security to achieve real-time maritime awareness in military and civilian domains. However, most existing vessel monitoring models tend to focus on a single remote sensing...