Statements (29)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
neural network module
|
| gptkbp:appliesTo |
spatial attention
channel attention |
| gptkbp:category |
attention mechanism
|
| gptkbp:citation |
over 4000
|
| gptkbp:doi |
10.1007/978-3-030-01234-2_1
|
| gptkbp:fullName |
Convolutional Block Attention Module
|
| https://www.w3.org/2000/01/rdf-schema#label |
CBAM
|
| gptkbp:improves |
image classification
segmentation object detection |
| gptkbp:input |
feature map
|
| gptkbp:integratesWith |
gptkb:ResNet
gptkb:DenseNet gptkb:MobileNet |
| gptkbp:language |
gptkb:Python
|
| gptkbp:openSource |
gptkb:GitHub
|
| gptkbp:output |
refined feature map
|
| gptkbp:proposedBy |
Sanghyun Woo
In So Kweon Jongchan Park Joon-Young Lee |
| gptkbp:publishedIn |
ECCV 2018
|
| gptkbp:purpose |
improve feature representation in CNNs
|
| gptkbp:url |
https://arxiv.org/abs/1807.06521
|
| gptkbp:usedIn |
computer vision
|
| gptkbp:bfsParent |
gptkb:Squeeze-and-Excitation_Networks
gptkb:Carbon_Border_Adjustment_Mechanism |
| gptkbp:bfsLayer |
7
|