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81 lines
2.7 KiB
81 lines
2.7 KiB
3 years ago
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# (Tensorflow) Inception v3
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3 years ago
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**Inception v3** is a convolutional neural network architecture from the Inception family that makes several improvements including using [Label Smoothing](https://paperswithcode.com/method/label-smoothing), Factorized 7 x 7 convolutions, and the use of an [auxiliary classifer](https://paperswithcode.com/method/auxiliary-classifier) to propagate label information lower down the network (along with the use of batch normalization for layers in the sidehead). The key building block is an [Inception Module](https://paperswithcode.com/method/inception-v3-module).
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3 years ago
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The weights from this model were ported from [Tensorflow/Models](https://github.com/tensorflow/models).
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3 years ago
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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{DBLP:journals/corr/SzegedyVISW15,
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author = {Christian Szegedy and
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Vincent Vanhoucke and
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Sergey Ioffe and
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Jonathon Shlens and
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Zbigniew Wojna},
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title = {Rethinking the Inception Architecture for Computer Vision},
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journal = {CoRR},
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volume = {abs/1512.00567},
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year = {2015},
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url = {http://arxiv.org/abs/1512.00567},
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archivePrefix = {arXiv},
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eprint = {1512.00567},
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timestamp = {Mon, 13 Aug 2018 16:49:07 +0200},
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biburl = {https://dblp.org/rec/journals/corr/SzegedyVISW15.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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```
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<!--
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Models:
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- Name: tf_inception_v3
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Metadata:
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FLOPs: 7352418880
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Training Data:
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- ImageNet
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Training Techniques:
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- Gradient Clipping
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- Label Smoothing
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- RMSProp
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- Weight Decay
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Training Resources: 50x NVIDIA Kepler GPUs
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Architecture:
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- 1x1 Convolution
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- Auxiliary Classifier
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- Average Pooling
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inception-v3 Module
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- Max Pooling
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- ReLU
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- Softmax
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File Size: 95549439
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Tasks:
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- Image Classification
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ID: tf_inception_v3
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LR: 0.045
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Dropout: 0.2
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '299'
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/inception_v3.py#L449
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In Collection: TF Inception v3
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Collections:
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- Name: TF Inception v3
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Paper:
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title: Rethinking the Inception Architecture for Computer Vision
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3 years ago
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url: https://paperswithcode.com//paper/rethinking-the-inception-architecture-for
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3 years ago
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type: model-index
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Type: model-index
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-->
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