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


阿小庆 2018-06-24 17:11


飞翔 2019-05-31 17:22

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


no_speaking 2018-06-17 00:47
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汪汪汪 2018-05-22 14:55
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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