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# Res2NeXt
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**Res2NeXt** is an image model that employs a variation on [ResNeXt](https://paperswithcode.com/method/resnext) bottleneck residual blocks. The motivation is to be able to represent features at multiple scales. This is achieved through a novel building block for CNNs that constructs hierarchical residual-like connections within one single residual block. This represents multi-scale features at a granular level and increases the range of receptive fields for each network layer.
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{% include 'code_snippets.md' %}
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## How do I train this model?
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You can follow the [timm recipe scripts](https://rwightman.github.io/pytorch-image-models/scripts/) for training a new model afresh.
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## Citation
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```BibTeX
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@article{Gao_2021,
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title={Res2Net: A New Multi-Scale Backbone Architecture},
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volume={43},
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ISSN={1939-3539},
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url={http://dx.doi.org/10.1109/TPAMI.2019.2938758},
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DOI={10.1109/tpami.2019.2938758},
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number={2},
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journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
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publisher={Institute of Electrical and Electronics Engineers (IEEE)},
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author={Gao, Shang-Hua and Cheng, Ming-Ming and Zhao, Kai and Zhang, Xin-Yu and Yang, Ming-Hsuan and Torr, Philip},
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year={2021},
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month={Feb},
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pages={652–662}
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}
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```
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<!--
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Models:
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- Name: res2next50
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Metadata:
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FLOPs: 5396798208
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Epochs: 100
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Batch Size: 256
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 4x Titan Xp GPUs
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Architecture:
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- Batch Normalization
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- Convolution
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- Global Average Pooling
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- ReLU
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- Res2NeXt Block
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File Size: 99019592
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Tasks:
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- Image Classification
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ID: res2next50
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LR: 0.1
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/res2net.py#L207
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In Collection: Res2NeXt
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Collections:
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- Name: Res2NeXt
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Paper:
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title: 'Res2Net: A New Multi-scale Backbone Architecture'
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url: https://paperswithcode.com//paper/res2net-a-new-multi-scale-backbone
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type: model-index
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Type: model-index
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-->
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