课程回顾-Convolutional Neural Networks

【课程回顾-Convolutional Neural Networks】的更多相关文章

课程回顾-Convolutional Neural Networks

为什么卷积层计算量更低paddingStrided convolution多维卷积LeNet 参数卷积网络的好处参数共享稀疏连接经典网络实现LeNet-5AlexNetVGGResNet残差块identity blockconvolutional block残差网络为什么残差网络有用Network in Network & 1*1 convolutionsInception network motivationGoogleNetData AugmentationObject Detection几…

课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 3.Programming assignments：Convolutional Model: application

Convolutional Neural Networks: Application Welcome to Course 4's second assignment! In this notebook, you will: Implement helper functions that you will use when implementing a TensorFlow model Implement a fully functioning ConvNet using TensorFlow (…

课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 2.Programming assignments：Convolutional Model: step by step

Convolutional Neural Networks: Step by Step Welcome to Course 4's first assignment! In this assignment, you will implement convolutional (CONV) and pooling (POOL) layers in numpy, including both forward propagation and (optionally) backward propagati…

课程四(Convolutional Neural Networks)，第四周（Special applications: Face recognition & Neural style transfer） —— 2.Programming assignments：Art generation with Neural Style Transfer

Deep Learning & Art: Neural Style Transfer Welcome to the second assignment of this week. In this assignment, you will learn about Neural Style Transfer. This algorithm was created by Gatys et al. (2015) (https://arxiv.org/abs/1508.06576). In this as…

课程四(Convolutional Neural Networks)，第二周（Deep convolutional models: case studies） —— 0.Learning Goals

Learning Goals Understand multiple foundational papers of convolutional neural networks Analyze the dimensionality reduction of a volume in a very deep network Understand and Implement a Residual network Build a deep neural network using Keras Implem…

课程四(Convolutional Neural Networks)，第二周（Deep convolutional models: case studies） ——3.Programming assignments : Residual Networks

Residual Networks Welcome to the second assignment of this week! You will learn how to build very deep convolutional networks, using Residual Networks (ResNets). In theory, very deep networks can represent very complex functions; but in practice, the…

课程四(Convolutional Neural Networks)，第二周（Deep convolutional models: case studies） —— 2.Programming assignments : Keras Tutorial - The Happy House (not graded)

Keras tutorial - the Happy House Welcome to the first assignment of week 2. In this assignment, you will: Learn to use Keras, a high-level neural networks API (programming framework), written in Python and capable of running on top of several lower-l…

课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 0.Learning Goals

Learning Goals Understand the convolution operation Understand the pooling operation Remember the vocabulary used in convolutional neural network (padding, stride, filter, ...) Build a convolutional neural network for image multi-class classification…

课程四(Convolutional Neural Networks)，第四周（Special applications: Face recognition & Neural style transfer） —— 3.Programming assignments：Face Recognition for the Happy House

Face Recognition for the Happy House Welcome to the first assignment of week 4! Here you will build a face recognition system. Many of the ideas presented here are from FaceNet. In lecture, we also talked about DeepFace. Face recognition problems com…

课程四(Convolutional Neural Networks)，第四周（Special applications: Face recognition & Neural style transfer） —— 1.Practice quentions

[解释] This allows us to learn to predict a person’s identity using a softmax output unit, where the number of classes equals the number of persons in the database plus 1 (for the final “not in database” class). 上述选项错误的原因: 1.plus 1的解释错误: 将某人的照片放进卷积神经网络…