文件名称：卷积神经网络相关论文资料
文件大小：65.52MB
文件格式：ZIP
更新时间：2019-09-18 10:27:43
cnn 卷积神经网络 cnn论文
关于卷积神经网络的多篇论文资料，基本都是很有价值，2016最新的论文。有些看过的做了标注，其余的粗略看过。如果有什么问题或疑问，可以通过csdn博客联系我。
【文件预览】：
深入研究CNN系列论文
----5Must Know Tips_Tricks in Deep Neural Networks.pdf(1.42MB)
----Adadelta-An Adaptive Learning Rate Method.pdf(524KB)
----5A Novel Sparse Autoencoder for Modeling High-dimensional Sensory Data.pdf(360KB)
----2Learning convolutional feature hierarchies for visual recognition.pdf(419KB)
----3k-Sparse Autoencoders.pdf(719KB)
----Network In Network.pdf(581KB)
----Deep Big Simple Neural Nets Excel on Handwritten.pdf(293KB)
----Learning Deep State Representations With Convolutional.pdf(549KB)
----3Visualizing and understanding convolutional networks.pdf(2.2MB)
----1discriminative unsupervised feature-learning with convolutional neural networks.pdf(366KB)
----StrongNet-mostly unsupervised image recognition with strong neurons.pdf(254KB)
----1Stacked Autoencoders for Unsupervised Feature Learning and Multiple Organ Detection in a Pilot Study Using 4D Patient Data.pdf(3.7MB)
----Fractional Max-Pooling.pdf(634KB)
----The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization.pdf(253KB)
----1Maxout Networks.pdf(1022KB)
----5sparse filtering.pdf(413KB)
----Learning Activation Functions to Improve Deep Neural Networks.pdf(690KB)
----Unsupervised Deep Feature Extraction for Remote Sensing Image Classification.pdf(2.63MB)
----Batch-normalized Maxout Network in Network.pdf(668KB)
----5Reducing the Dimensionality of Data with Neural Networks.pdf(367KB)
----Extracting and Composing Robust Features with Denoising Autoencoders.pdf(515KB)
----ReNet-A Recurrent Neural Network Based Alternative to Convolutional Networks.pdf(1.18MB)
----Neocognitron-A self organizing neural network.pdf(1.06MB)
----Competitive Multi-scale Convolution.pdf(2.44MB)
----Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis.pdf(291KB)
----Gradient-based learning applied to document recognition.pdf(889KB)
----Supplementary Material for Sparse Filtering.pdf(53KB)
----Convolutional Kernel Networks.pdf(187KB)
----Building High-Level Features Using Large Scale Unsupervised Learning.pdf(3.66MB)
----Adaptive Deconvolutional Networks for Mid and High Level Feature Learning.pdf(4.15MB)
----Deep learning face representation from predicting.pdf(2.5MB)
----1Spatially-sparse convolutional neural networks.pdf(472KB)
----2Autoencoders-for-image-classification.pdf(2.44MB)
-----efficient learning of sparse representations with an energy based model.pdf(137KB)
----5Winner-Take-All Autoencoders.pdf(1.33MB)
----Adaptive Subgradient Methods for online learning and stochastic optimization.pdf(448KB)
----Generalizing Pooling Functions in Convolutional Neural Networks Mixed, Gated, and Tree.pdf(780KB)
----An Analysis of Single-Layer Networks in Unsupervised Feature Learning.pdf(889KB)
----4Stacked What-Where Auto-Encoders.pdf(611KB)
----Delving Deep into Rectifiers-Surpassing Human-Level Performance on ImageNet Classification.pdf(2.18MB)
----卷积神经网络调研.pdf(2.23MB)
----Combined genetic algorithm optimization and regularizedorthogonal least.pdf(2.63MB)
----Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUS).pdf(792KB)
----Deeply-Supervised Nets.pdf(786KB)
----Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations.pdf(892KB)
----5Deconvolutional Networks.pdf(1.95MB)
----5Convolutional Clustering for Unsupervised Learning.pdf(645KB)
----Recurrent Convolutional Neural Network for Object Recognition.pdf(551KB)
----3Stacked Convolutional Auto-Encoders for hierarchical feature extraction.pdf(760KB)
----5Striving for Simplicity the all Convolutional net.pdf(4MB)
----ImageNet Classification with Deep Convolutional.pdf(1.35MB)
----Deconvolutional slides.pdf(5.81MB)
----4Deep Convolutional Neural Networks as Generic Feature Extractors.pdf(515KB)
----On random weights and unsupervised feature learning.pdf(828KB)
----Large scale distributed deep networks.pdf(263KB)
----On the Importance of Normalisation Layers in Deep Learning with Piecewise Linear Activation Units.pdf(2.14MB)
----Multi-column Deep Neural Networks for Image Classification.pdf(1.59MB)