Going Deeper with Convolutions

辉仔 2018-01-10 11:12
We propose a deep convolutional neural network architecture codenamed "Inception", which was responsible for setting the new state of the art for classification and detection in the ImageNet Large-Sca

1吴恩达Meachine-Learing之监督学习和非监督学习

阿小庆 2018-06-24 17:11
介绍监督学习和非监督学习的区别。

pytorch应用之——纸币识别(一)

飞翔 2019-05-31 17:22
这里数据集一共有39620张,而且背景单一,所以纸币面值的识别不是一个很难的问题。我用resnet18(自己稍微改了一些结构,影响不大)去训练这个数据集,迭代24次可以达到99.96%的精度。

Very Deep Convolutional Networks for Large-Scale Image Recognition

辉仔 2018-01-10 10:31
In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evaluation of networks of in

Identity Mappings in Deep Residual Networks

jixiaohui 2018-01-10 12:10
Deep residual networks have emerged as a family of extremely deep architectures showing compelling accuracy and nice convergence behaviors. In this paper, we analyze the propagation formulations behin

One weird trick for parallelizing convolutional neural networks

辉仔 2018-01-10 10:26
I present a new way to parallelize the training of convolutional neural networks across multiple GPUs. The method scales significantly better than all alternatives when applied to modern convolutional

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

jixiaohui 2018-01-10 14:52
We present a class of efficient models called MobileNets for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses depth-wise separable convolutions to

分类与聚类的区别

no_speaking 2018-06-17 00:47
分类与聚类的区别
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读论文-AlignedReID

汪汪汪 2018-05-22 14:55
拜读旷世的论文
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Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

辉仔 2018-01-10 11:09
In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications. Comparatively, unsupervised learning with CNNs has received less attenti
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