LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
GPTKB entity
Statements (22)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic_journal
|
| gptkbp:application |
autonomous driving
scene understanding real-time semantic segmentation |
| gptkbp:arXivID |
1707.03718
|
| gptkbp:author |
Abhishek Chaurasia
Eugenio Culurciello |
| gptkbp:benchmarkDataset |
gptkb:CamVid
gptkb:Cityscapes |
| gptkbp:field |
computer vision
semantic segmentation |
| gptkbp:focusesOn |
efficient semantic segmentation
|
| gptkbp:hasMethod |
gptkb:LinkNet
|
| https://www.w3.org/2000/01/rdf-schema#label |
LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
|
| gptkbp:proposedBy |
efficient encoder-decoder network
|
| gptkbp:publicationYear |
2017
|
| gptkbp:publishedIn |
gptkb:arXiv
|
| gptkbp:requires |
faster inference with competitive accuracy
|
| gptkbp:url |
https://arxiv.org/abs/1707.03718
|
| gptkbp:uses |
encoder-decoder architecture
|
| gptkbp:bfsParent |
gptkb:LinkNet
|
| gptkbp:bfsLayer |
8
|