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fast-rcnn-master
- Fast Region-based Convolutional Networks for object detection. Fast R-CNN** is a fast framework for object detection with deep ConvNets. Fast R-CNN - trains state-of-the-art models, like VGG16, 9x faster than traditional R-CNN and 3x faster than
vgg16
- 在使用深度神经网络时我们一般推荐使用大牛的组推出的和成功的网络。如最近的google团队推出的BN-inception网络和inception-v3以及微软最新的深度残差网络ResNET。(In the use of deep neural network we generally recommend the use of cattle group launched and successful network. Such as the recent google team launched B
利用tensorflow编写的vgg16网络跑cifar10
- 利用tensorflow编写的vgg16网络跑cifar10，使用python语言，精确度较高.
tensorflow-vgg16-train-and-test-master
- vgg深度学习，图像识别，用于图像的分类，在python上运行(vgg deep learning, image recognition, used for image classification, running on Python)
使用vgg16训练cifar数据集
- 神经网络 深度学习 慕课平台 tensorflow2.1 使用vgg16训练cifar10分类数据集