MoCo-AIS is a MoCo-based contrastive learning framework that learns vessel trajectory embeddings and improves similarity computation over baselines on large-scale real-world AIS datasets while offering a benchmarking platform.
Jensen, and Jianzhong Qi
2 Pith papers cite this work. Polarity classification is still indexing.
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ANN search quality is better assessed by 1/Ratio@k than Recall@k because the former tracks downstream task utility more closely while allowing substantially lower computational cost.
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MoCo-AIS: A Contrastive Learning Framework for Similarity Computation of Vessel Trajectories
MoCo-AIS is a MoCo-based contrastive learning framework that learns vessel trajectory embeddings and improves similarity computation over baselines on large-scale real-world AIS datasets while offering a benchmarking platform.
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ANN Search: Recall What Matters
ANN search quality is better assessed by 1/Ratio@k than Recall@k because the former tracks downstream task utility more closely while allowing substantially lower computational cost.