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Table 1 Vessel verification results on 50,000 positive pairs and 50,000 negative pairs of vessels for the nearest neighbor and SVM classifiers by utilizing the generic and end-to-end learning-based vessel representations learned in IMO training set, which does not contain any images of the vessels in IMO test set

From: Generic and attribute-specific deep representations for maritime vessels

  Representation True positives True negatives False positives False negatives Accuracy Precision Recall
NN 109-dimensional output based 44,978 40,198 9,802 5,022 85.18% 0.82 0.90
SVM 109-dimensional output based 45,503 45,422 4,578 4,497 90.93% 0.91 0.91
NN 4144-dimensional output based 47,305 41,148 8,852 2,695 88.45% 0.84 0.95
SVM 4144-dimensional output based 46,225 47,744 2,256 3,775 93.97% 0.95 0.92
NN Siamese network based 44,459 40,390 9,610 5,541 84.85% 0.82 0.89
SVM Siamese network based 45,869 46,150 3,850 4,131 92.02% 0.92 0.92