Convolutional Neural Networks
CSPDarknet53
Introduced by Bochkovskiy et al. in YOLOv4: Optimal Speed and Accuracy of Object DetectionCSPDarknet53 is a convolutional neural network and backbone for object detection that uses DarkNet-53. It employs a CSPNet strategy to partition the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The use of a split and merge strategy allows for more gradient flow through the network.
This CNN is used as the backbone for YOLOv4.
Source: YOLOv4: Optimal Speed and Accuracy of Object Detection
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Object Detection | 80 | 24.77% |
| Object | 44 | 13.62% |
| Real-Time Object Detection | 17 | 5.26% |
| Autonomous Driving | 9 | 2.79% |
| Deep Learning | 9 | 2.79% |
| 2D Object Detection | 7 | 2.17% |
| Object Tracking | 7 | 2.17% |
| Multi-Object Tracking | 6 | 1.86% |
| Semantic Segmentation | 6 | 1.86% |
Darknet-53
