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!7785 Update ModelZoo README and googlenet README files
From: @liyanliu96 Reviewed-by: @oacjiewen,@yingjy,@oacjiewen Signed-off-by: @yingjytags/v1.1.0
mindspore-ci-bot
Gitee
5 years ago
2 changed files with 6 additions and 6 deletions
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model_zoo/README.md
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| @@ -27,16 +27,16 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | |||||
| - [AlexNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet/README.md) | - [AlexNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet/README.md) | ||||
| - [LeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet/README.md) | - [LeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet/README.md) | ||||
| - [LeNet_Quant](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet_quant/README.md) | - [LeNet_Quant](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet_quant/README.md) | ||||
| - [InceptionV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3/README.md) | |||||
| - [MobileNetV2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2/README.md) | |||||
| - [MobileNetV2_Quant](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2_quant/README.md) | |||||
| - [MobileNetV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv3/README.md) | |||||
| - [InceptionV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3/README.md) | |||||
| - [Object Detection and Segmentation](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv) | - [Object Detection and Segmentation](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv) | ||||
| - [DeepLabV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeplabv3/README.md) | - [DeepLabV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeplabv3/README.md) | ||||
| - [FasterRCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn/README.md) | - [FasterRCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn/README.md) | ||||
| - [YoloV3-DarkNet53](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53/README.md) | - [YoloV3-DarkNet53](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53/README.md) | ||||
| - [YoloV3-ResNet18](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18/README.md) | - [YoloV3-ResNet18](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18/README.md) | ||||
| - [MobileNetV2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2/README.md) | |||||
| - [MobileNetV2_Quant](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2_quant/README.md) | |||||
| - [MobileNetV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv3/README.md) | |||||
| - [MaskRCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn/README.md) | |||||
| - [MaskRCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn/README.md) | |||||
| - [SSD](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd/README.md) | - [SSD](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd/README.md) | ||||
| - [Warp-CTC](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc/README.md) | - [Warp-CTC](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc/README.md) | ||||
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model_zoo/official/cv/googlenet/README.md
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| @@ -36,7 +36,7 @@ GoogleNet, a 22 layers deep network, was proposed in 2014 and won the first plac | |||||
| # [Model Architecture](#contents) | # [Model Architecture](#contents) | ||||
| Specifically, the GoogleNet contains numerous inception modules, which are connected together to go deeper. In general, an inception module with dimensionality reduction consists of **1×1 conv**, **3×3 conv**, **5×5 conv**, and **3×3 max pooling**, which are done altogether for the previous input, and stack together again at output. | |||||
| Specifically, the GoogleNet contains numerous inception modules, which are connected together to go deeper. In general, an inception module with dimensionality reduction consists of **1×1 conv**, **3×3 conv**, **5×5 conv**, and **3×3 max pooling**, which are done altogether for the previous input, and stack together again at output. In our model architecture, the kernel size used in inception module is 3×3 instead of 5×5. | |||||