You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
73 lines
2.1 KiB
73 lines
2.1 KiB
# CSP ResNeXt
|
|
|
|
**CSPResNeXt** is a convolutional neural network where we apply the Cross Stage Partial Network (CSPNet) approach to [ResNeXt](https://paperswithcode.com/method/resnext). The CSPNet partitions 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.
|
|
|
|
{% include 'code_snippets.md' %}
|
|
|
|
## How do I train this model?
|
|
|
|
You can follow the [timm recipe scripts](https://rwightman.github.io/pytorch-image-models/scripts/) for training a new model afresh.
|
|
|
|
## Citation
|
|
|
|
```BibTeX
|
|
@misc{wang2019cspnet,
|
|
title={CSPNet: A New Backbone that can Enhance Learning Capability of CNN},
|
|
author={Chien-Yao Wang and Hong-Yuan Mark Liao and I-Hau Yeh and Yueh-Hua Wu and Ping-Yang Chen and Jun-Wei Hsieh},
|
|
year={2019},
|
|
eprint={1911.11929},
|
|
archivePrefix={arXiv},
|
|
primaryClass={cs.CV}
|
|
}
|
|
```
|
|
|
|
<!--
|
|
Models:
|
|
- Name: cspresnext50
|
|
Metadata:
|
|
FLOPs: 3962945536
|
|
Batch Size: 128
|
|
Training Data:
|
|
- ImageNet
|
|
Training Techniques:
|
|
- Label Smoothing
|
|
- Polynomial Learning Rate Decay
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 1x GPU
|
|
Architecture:
|
|
- 1x1 Convolution
|
|
- Batch Normalization
|
|
- Convolution
|
|
- Global Average Pooling
|
|
- Grouped Convolution
|
|
- Max Pooling
|
|
- ReLU
|
|
- ResNeXt Block
|
|
- Residual Connection
|
|
- Softmax
|
|
File Size: 82562887
|
|
Tasks:
|
|
- Image Classification
|
|
Training Time: ''
|
|
ID: cspresnext50
|
|
LR: 0.1
|
|
Layers: 50
|
|
Crop Pct: '0.875'
|
|
Momentum: 0.9
|
|
Image Size: '224'
|
|
Weight Decay: 0.005
|
|
Interpolation: bilinear
|
|
Training Steps: 8000000
|
|
Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/cspnet.py#L430
|
|
Config: ''
|
|
In Collection: CSP ResNeXt
|
|
Collections:
|
|
- Name: CSP ResNeXt
|
|
Paper:
|
|
title: 'CSPNet: A New Backbone that can Enhance Learning Capability of CNN'
|
|
url: https://paperswithcode.com//paper/cspnet-a-new-backbone-that-can-enhance
|
|
type: model-index
|
|
Type: model-index
|
|
-->
|