Chatfield, K., Simonyan, K., Vedaldi, A., and Zisserman, A. Return of the devil in the details: Delving deep into convolutional nets. In Proc. BMVC., 2014. Cimpoi, M., Maji, S., and Vedaldi, A. Deep convolutional filter banks for texture recognition and segmentation. CoRR, abs/141...
The encoder neural network includes a time reduction subnetwork, a convolutional LSTM subnetwork, and a network in network subnetwork. The decoder neural network receives the encoded sequence and processes the encoded sequence to generate, for each position in an output sequence order, a set of ...
[1]. Simonyan K, Zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. [2]. Krizhevsky A, Sutskever I, Hinton G E. Imagenet classification with deep convolutional neural networks[C]//Advances in neural information processing...
COMPRESSION OF DEEP CONVOLUTIONAL NEURAL NETWORKS FOR FAST AND LOW POWER MOBILE APPLICATIONS【ICLR 2016】 SIGAI学习与实践平台 2019/03/11 1.1K0 Efficient Convolutional Neural Networks for Mobile Vision Applications 卷积神经网络神经网络 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...
Very Deep Convolutional Networks for Large-Scale Image Recognition 摘要 在这项工作中,我们研究了卷积网络深度在大规模的图像识别环境下对准确性的影响。我们的主要贡献是使用非常小的(3×3)卷积滤波器架构对网络深度的增加进行了全面评估,这表明通过将深度推到16-19加权层可以实现对现有技术配置的显著改进。这些发...
ConvolutionalNetworksforLarge-ScaleImageRecognition.提到LRN基本没什么用。 在Alexnet模型中首次提出这个概念。 参考文献: [LRN]:ImageNet Classification withDeepConvolutionalNeuralNetworks VGG网络结构 论文: 《VERYDEEPCONVOLUTIONALNETWORK SFORLARGE-SCALEIMAGERECOGNITION》 VGG16和VGG19模型是一种十分强大的分类模型,属于...
Convolutional neural networks (CNNs) are a standard component of many current state-of-the-art Large Vocabulary Continuous Speech Recognition (LVCSR) syste... Sercu, T,Puhrsch, C,Kingsbury, B,... - IEEE 被引量: 133发表: 2016年 Advances in Very Deep Convolutional Neural Networks for LVCSR ...
Abstract: 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 increasing depth using an architecture with very small (3x3) convolution filters, which ...
Deep Convolutional Neural Networks for Large-scale Speech Tasks 热度: 曹旭东 A practical theory for designing very deep convolutional neural networks 热度: a r X i v : 1 4 0 9 . 1 5 5 6 v 6 [ c s . C V ] 1 0 A p r
Very Deep Convolutional Networks for Large-Scale Image Recognition翻译 上 code 4 CLASSIFICATION EXPERIMENTS 4分类实验 Dataset. In this section, we present the image classification results achieved by the described ConvNet architectures on the ILSVRC-2012 dataset (which was used for ILSVRC 2012–2014...