mAP: 96.2
Papers with Code · CC BY-SA 4.0
Multi-Label Classification
Multi-Label Classification is the supervised learning problem where an instance may be associated with multiple labels. This is an extension of single-label classification (i.e., multi-class, or binary) where each instance is only associated with a single class label.
<span class="description-source">Source: Deep Learning for Multi-label Classification </span>
논문
mAP: 93.54
mAP: 88.4
mAP: 90.3
mAP: 90.3
F1-score: 92.41
GKGNet: Group K-Nearest Neighbor based Graph Convolutional Network for Multi-Label Image Recognition
mAP: 87.7
mAP: 89.8
mAP: 91.4
mAP: 90.0
mAP: 85.2
mAP: 91.30
mAP: 92.4
mAP: 94.3
mAP: 87.5
mAP: 86.0