inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5
可用于keras，tensorflow.keras，特征提取与迁移学习
2019-12-21 21:36:05
77.23MB
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vgg16_weights_tf_dim_ordering_tf_kernels_notop,Keras VGG16
2019-12-21 21:24:04
52.2MB
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kares VGG19神经网络参数vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5
2019-12-21 21:19:10
76.42MB
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resnet50_weights_tf_dim_ordering_tf_kernels_notop
Linux下是放在“~/.keras/models/”中
Win下则放在Python的“settings/.keras/models/”中
Windows-weights路径：C:\Users\你的用户名\.keras\models anaconda下依然好用
2019-12-21 21:17:26
83.48MB
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Supervised Hashing with Kernels
简单的介绍了KSH（基于核函数的监督哈希）
主要分以下几部分内容
1.Kernel-Based Supervised Hashing
2.Hash Functions with Kernels
3.Supervised Infromation
4.Code Inner Products
5.Greedy Optimization
6.Spectral Relaxation
7.Sigmoid Smoothing
2019-12-21 20:08:34
2.11MB
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Learning with Kernels - Support Vector Machines
2019-12-21 19:38:51
39.14MB
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keras下基于tensorflow的VGG16模型notop权重系数h5文件
2019-12-13 19:30:57
56.16MB
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