【论文阅读】Aggregated Residual Transformations for Deep Neural Networks Saining（ResNext） - 代码天地

【论文阅读】Aggregated Residual Transformations for Deep Neural Networks Saining（ResNext）

其他 2018-12-29 03:14:16 阅读次数: 0

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转载自blog.csdn.net/u013859301/article/details/80163850

【论文阅读】Aggregated Residual Transformations for Deep Neural Networks Saining（ResNext）

ResNeXt : Aggregated Residual Transformations for Deep Neural Networks

ResNeXt - Aggregated Residual Transformations for Deep Neural Networks

ResNeXt：Aggregated Residual Transformations for Deep Neural Networks

《2017-Aggregated Residual Transformations for Deep Neural Networks》论文阅读

Aggregated Residual Transformations for Deep Neural Networks

『Aggregated Residual Transformations for Deep Neural Networks』论文笔记

Aggregated Residual Transformations for DeepNeural Networks -ResNetXt2017【论文理解】

论文阅读|ResNetv2:Identity Mappings in Deep Residual Networks

【论文阅读笔记】---《A Survey of Model Compression and Acceleration for Deep Neural Networks》

【论文阅读笔记】Deep Neural Networks for Object Detection

【论文阅读】Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffma

【论文阅读】Clustering Convolutional Kernels to Compress Deep Neural Networks

论文阅读：Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks

【论文阅读】Gradient Centralization: A New Optimization Technique for Deep Neural Networks

论文阅读之《DeepIlluminance: Contextual IlluminanceEstimation via Deep Neural Networks》

读论文：Deep Neural Networks with Multitask Learning

解密ResNet：Identity Mappings in Deep Residual Networks论文笔记

Identity Mappings in Deep Residual Networks2016【论文理解】

Deep Residual Networks（ResNet）简介

Identity Mappings in Deep Residual Networks

Improving Deep Neural Networks

Neural Networks and Deep Learning

Efficient Deep Neural Networks

《Enhanced Deep Residual Networks for Single Image Super-Resolution》论文阅读之EDSR

[论文理解] Why do deep convolutional networks generalize so poorly to small image transformations?

【阅读笔记】Training Deep Neural Networks on Imbalanced Data Sets

Flower classification using deep convolutional neural networks 阅读笔记

Neural networks and deep learning阅读笔记（2）后向传播算法

《FRACTALNET: ULTRA-DEEP NEURAL NETWORKS WITHOUT RESIDUALS》阅读笔记

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