Keras tensorflow Resnet模型

小灰灰 2022-12-27 07:26 272阅读 0赞

# Resnet相关文章整理 #

## 1、Keras大法（9）——实现ResNet-34模型 ##

[https://blog.csdn.net/weixin\_42499236/article/details/87919919][https_blog.csdn.net_weixin_42499236_article_details_87919919]

*  [（1）模型结构][1]
 *  [（2）模型代码][2]
 *  [（3）总 结][3_]

## 2、tensorflow手动复现论文中的Resnet34结构（不借助keras和slim模块） ##

[https://blog.csdn.net/Exploer\_TRY/article/details/89308329][https_blog.csdn.net_Exploer_TRY_article_details_89308329]

## 3、ResNet在分别在Keras和tensorflow框架下的应用案例 ##

[https://blog.csdn.net/weixin\_41923961/article/details/83057184][https_blog.csdn.net_weixin_41923961_article_details_83057184]

## 4、Tensorflow2.0 keras ResNet18 34 50 101 152系列 代码实现 ##

[https://blog.csdn.net/Forrest97/article/details/106136435?utm\_medium=distribute.pc\_relevant.none-task-blog-searchFromBaidu-3.control&depth\_1-utm\_source=distribute.pc\_relevant.none-task-blog-searchFromBaidu-3.control][https_blog.csdn.net_Forrest97_article_details_106136435_utm_medium_distribute.pc_relevant.none-task-blog-searchFromBaidu-3.control_depth_1-utm_source_distribute.pc_relevant.none-task-blog-searchFromBaidu-3.control]

## 5、[关于深度残差网络（Deep residual network, ResNet）][Deep residual network_ ResNet] ##

[https://www.cnblogs.com/Ann21/p/9825602.html][Deep residual network_ ResNet]

## 6、Introduction to Keras for Researchers ##

[https://keras.io/getting\_started/intro\_to\_keras\_for\_researchers/][https_keras.io_getting_started_intro_to_keras_for_researchers]

## 7、Introduction to ResNet in TensorFlow 2 ##

[https://adventuresinmachinelearning.com/introduction-resnet-tensorflow-2/][https_adventuresinmachinelearning.com_introduction-resnet-tensorflow-2]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FpbmdmZW5neGQx_size_16_color_FFFFFF_t_70][]

[https_blog.csdn.net_weixin_42499236_article_details_87919919]: https://blog.csdn.net/weixin_42499236/article/details/87919919
[1]: https://blog.csdn.net/weixin_42499236/article/details/87919919#1_2
[2]: https://blog.csdn.net/weixin_42499236/article/details/87919919#2_5
[3_]: https://blog.csdn.net/weixin_42499236/article/details/87919919#3____94
[https_blog.csdn.net_Exploer_TRY_article_details_89308329]: https://blog.csdn.net/Exploer_TRY/article/details/89308329
[https_blog.csdn.net_weixin_41923961_article_details_83057184]: https://blog.csdn.net/weixin_41923961/article/details/83057184
[https_blog.csdn.net_Forrest97_article_details_106136435_utm_medium_distribute.pc_relevant.none-task-blog-searchFromBaidu-3.control_depth_1-utm_source_distribute.pc_relevant.none-task-blog-searchFromBaidu-3.control]: https://blog.csdn.net/Forrest97/article/details/106136435?utm_medium=distribute.pc_relevant.none-task-blog-searchFromBaidu-3.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-searchFromBaidu-3.control
[Deep residual network_ ResNet]: https://www.cnblogs.com/Ann21/p/9825602.html
[https_keras.io_getting_started_intro_to_keras_for_researchers]: https://keras.io/getting_started/intro_to_keras_for_researchers/
[https_adventuresinmachinelearning.com_introduction-resnet-tensorflow-2]: https://adventuresinmachinelearning.com/introduction-resnet-tensorflow-2/
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FpbmdmZW5neGQx_size_16_color_FFFFFF_t_70]: /images/20221120/09bddc5eec9342efa0881954a4063f05.png