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@ -134,43 +134,41 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework a
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| Parameters | AlexNet |
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| -------------------------- | ------- |
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| Published Year | |
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| Paper | |
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| Features | |
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| MindSpore Version | |
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| Training Parameters | |
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| Loss Function | |
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| Accuracy | |
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| Loss | |
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| Params (M) | |
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| Checkpoint for Fine tuning | |
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| Model for inference | |
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| Scripts | |
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| Published Year | 2012 |
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| Paper | [ImageNet Classification with Deep Convolutional Neural Networks](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-) |
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| Resource | Ascend 910 |
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| Features | support with Ascend, GPU |
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| MindSpore Version | 0.5.0-beta |
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| Dataset | CIFAR10 |
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| Training Parameters | epoch=30, batch_size=32 |
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| Optimizer | Momentum |
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| Loss Function | SoftmaxCrossEntropyWithLogits |
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| Accuracy | 88.23% |
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| Speed | 1481fps |
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| Loss | 0.108 |
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| Params (M) | 61.10 |
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| Checkpoint for Fine tuning | 445MB(.ckpt file) |
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| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/alexnet|
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#### [LeNet](#table-of-contents)
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| Parameters | LeNet |
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| -------------------------- | ----- |
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| Published Year | |
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| Paper | |
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| Features | |
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| MindSpore Version | |
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| Dataset | |
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| Training Parameters | |
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| Optimizer | |
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| Loss Function | |
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| Accuracy | |
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| Speed | |
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| Loss | |
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| Params (M) | |
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| Checkpoint for Fine tuning | |
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| Model for inference | |
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| Scripts | |
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| Published Year | 1998 |
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| Paper | [Gradient-Based Learning Applied to Document Recognition](https://ieeexplore.ieee.org/abstract/document/726791) |
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| Resource | Ascend 910 |
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| Features | support with Ascend, GPU, CPU |
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| MindSpore Version | 0.5.0-beta |
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| Dataset | MNIST |
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| Training Parameters | epoch=10, batch_size=32 |
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| Optimizer | Momentum |
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| Loss Function | SoftmaxCrossEntropyWithLogits |
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| Accuracy | 98.52% |
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| Speed | 18680fps |
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| Loss | 0.004 |
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| Params (M) | 0.06 |
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| Checkpoint for Fine tuning | 483KB(.ckpt file) |
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| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/lenet|
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### Object Detection and Segmentation
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