论文解读 《Quantized Convolutional Neural Networks for Mobile Devices》 论文地址:https://arxiv.org/abs/1512.06473...Chen.Compressing neural networks with the hashing trick....Speeding up convolutional neural networks with low rank expansions....Speeding-up convolutional neural networks using fine-tuned cp-decomposition....Data-free parameter pruning for deep neural networks.
我们提出了一类有效的模型称为移动和嵌入式视觉应用的移动网络。MobileNets是基于流线型架构,使用深度可分卷积来建立轻量级深度神经网络。我们介绍了两个简单的...
DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks ICCV2017 http://people.ee.ethz.ch...one, while being tolerant to small mismatches 3.1.2 Texture loss 这里我们使用一个 generative adversarial networks
计算机视觉(Computer Vision)包含很多不同类别的问题,如图片分类、目标检测、图片风格迁移等等。
= 0)对变量W1,W2进行初始化 def initialize_parameters(): """ Initializes weight parameters to build a neural
我们主要基于numpy实现 convolutional (CONV) and pooling (POOL) layers ,包括前向传播和反向传播。
我们训练了一个大型的深度卷积神经网络,将ImageNet lsvprc -2010竞赛中的120万幅高分辨率图像分成1000个不同的类。在测试数据上,我们实现了...
visual features(which may not always be present). 2 Related Work Data Augmentation for Images Dropout in Convolutional...Neural Networks Denoising Autoencoders & Context Encoders(self-supervised,挖去部分,网络补上,以强化特征) 3 Advantages...dropout 作用在 FC 上的效果比 Conv 上好,作者的解释是:1)convolutional layers already have much fewer parameters than fully-connected
cnn-text-classification-tf 作者theano实现: https://github.com/yoonkim/CNN_sentence 字符级CNN的论文:Character-level Convolutional...Networks for Text Classification
TextCnn 调参 参考论文:《A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks
实时、准确和健壮的瞳孔检测是普及的基于视频的眼球跟踪的必要前提。 然而,由于快速的光照变化、瞳孔遮挡、非中心和离轴眼记录以及眼的生理特征,在真实场景中自动检测瞳...
增加模型精度的方法有增加网络的深度,特征图的通道数以及分辨率(如下图a-d所示)。这篇文章研究了模型缩放,发现仔细平衡网络的深度、宽度和分辨率可以获得更好的性能...
Convolutional Neural Networks翻译为卷积神经网络,常用在图像识别和语音分析等领域。...CNN详细介绍参看: https://en.wikipedia.org/wiki/Convolutional_neural_network http://blog.csdn.net/zouxy09/article.../mnist_data/', one_hot=True) n_output_layer = 10 # 定义待训练的神经网络 def convolutional_neural_network(data...X = tf.placeholder('float', [None, 28 * 28]) Y = tf.placeholder('float') # 使用数据训练神经网络 def train_neural_network...(X, Y): predict = convolutional_neural_network(X) # cost_func = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits
这篇文章来自李沐大神团队,使用各种CNN tricks,将原始的resnet在imagenet上提升了四个点。记录一下,可以用到自己的网络上。如果图片显示不了,...
tags: cnn,图像分类,trick grammar_cjkRuby: true --- 以下内容摘自《Bag of Tricks for Image Classification with Convolutional...Neural Networks》。
其中第一部分主要包括: 利用Theano理解深度学习——Logistic Regression 利用Theano理解深度学习——Multilayer perceptron 利用Theano理解深度学习——Deep Convolutional...Network 一、CNN概述 卷积神经网络(Convolutional Neural Networks, CNN)是多层感知机MLP模型的一个变种,主要是受到生物学的启发。...参考文献 Convolutional Neural Networks (LeNet)http://www.deeplearning.net/tutorial/lenet.html#tips-and-tricks
Fully Convolutional Neural Networks for Crowd Segmentation https://arxiv.org/abs/1411.4464 这里设计了一个全卷积网络用于视频中的人群分割...feature fusion combines output feature maps of a certain fusion layer and use feature maps of all three networks...make a decision. 3)The decision fusion scheme combines the output maps of three separately trained networks
ImageNet Classification with Deep Convolutional Neural Networks Advances in Neural Information Processing
Sequential regulatory activity prediction across chromosomes with convolutional neural networks 基于卷积神经网络的染色体序列调控活动预测
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