
MatConvNet
 Referenced in 6 articles
[sw15651]
 MatConvNet – convolutional neural networks for MATLAB. MatConvNet is an open source implementation of Convolutional Neural ... MATLAB functions, providing routines for computing convolutions with filter banks, feature pooling, normalisation, and much...

Lasagne
 Referenced in 6 articles
[sw20936]
 neural networks in Theano. Its main features are: Supports feedforward networks such as Convolutional...

SegNet
 Referenced in 4 articles
[sw27575]
 novel and practical deep fully convolutional neural network architecture for semantic pixelwise segmentation termed ... engine consists of an encoder network, a corresponding decoder network followed by a pixelwise ... encoder network is topologically identical to the 13 convolutional layers in the VGG16 network...

DeepTracker
 Referenced in 2 articles
[sw25889]
 DeepTracker: Visualizing the Training Process of Convolutional Neural Networks. Deep convolutional neural networks (CNNs) have...

DeepFix
 Referenced in 2 articles
[sw25895]
 DeepFix: A Fully Convolutional Neural Network for predicting Human Eye Fixations. Understanding and predicting ... firstofitskind fully convolutional neural network for accurate saliency prediction. Unlike classical works ... account using network layers with very large receptive fields. Generally, fully convolutional nets are spatially...

iRNAPseKNC
 Referenced in 1 article
[sw27658]
 methylation sites by convolution neural network and Chou’s pseudo components. The 2’Omethylation ... proposed a simple and precise convolution neural network method namely: iRNAPseKNC(2methyl) to identify ... methylation using the proposed convolution neural network model. The proposed prediction iRNAPseKNC(2methyl) method...

FINNR
 Referenced in 1 article
[sw25906]
 Framework for Fast Exploration of Quantized Neural Networks. Convolutional Neural Networks have rapidly become...

cudaconvnet
 Referenced in 2 articles
[sw27213]
 Highperformance C++/CUDA implementation of convolutional neural networks...

fpgaConvNet
 Referenced in 1 article
[sw25907]
 fpgaConvNet: A framework for mapping Convolutional Neural Networks on FPGAs. Convolutional Neural Networks (ConvNets/CNNs...

DeepTrack
 Referenced in 2 articles
[sw27576]
 online for robust visual tracking. Deep neural networks, albeit their great success on feature learning ... robust tracking algorithm using a single Convolutional Neural Network (CNN) for learning effective feature representations...

SyncSpecCnn
 Referenced in 2 articles
[sw26163]
 vertex functions on them by convolutional neural networks, we resort to spectral CNN method that ... graph laplacian eigenbases. Under this setting, our network, named SyncSpecCNN, strive to overcome ... introduce a spectral parameterization of dilated convolutional kernels and a spectral transformer network. Experimentally...

DeepSleepNet
 Referenced in 2 articles
[sw21053]
 proposed model, we utilize Convolutional Neural Networks (CNNs) to extract timeinvariant features, and bidirectional...

BodaRTC
 Referenced in 1 article
[sw15267]
 Generation of Portable, Efficient Code for Convolutional Neural Networks on Mobile Computing Platforms. The popularity ... industry, and popular culture. In particular, convolutional neural networks (CNNs) have been applied to many...

JigsawNet
 Referenced in 1 article
[sw25887]
 JigsawNet: Shredded Image Reassembly using Convolutional Neural Network and Loopbased Composition. This paper proposes ... complicated puzzles. We build a deep convolutional neural network to detect the compatibility...

VIPLFaceNet
 Referenced in 1 article
[sw21624]
 which is a 10layer deep convolutional neural network with 7 convolutional layers...

QuasarNET
 Referenced in 1 article
[sw25901]
 Networks. We introduce QuasarNET, a deep convolutional neural network that performs classification and redshift estimation...

ConvS2S
 Referenced in 1 article
[sw26536]
 Sergey Edunov, Myle Ott, and Sam Gross. Convolutional Sequence to Sequence Learning. The prevalent approach ... variable length output sequence via recurrent neural networks ... introduce an architecture based entirely on convolutional neural networks. Compared to recurrent models, computations over...

ByteNet
 Referenced in 1 article
[sw26537]
 ByteNet is a onedimensional convolutional neural network that is composed of two parts ... decode the target sequence. The two network parts are connected by stacking the decoder ... convolutional layers to increase its receptive field. The resulting network has two core properties ... previous best results obtained with recurrent networks. The ByteNet also achieves state...

SalGAN
 Referenced in 1 article
[sw28155]
 Networks. We introduce SalGAN, a deep convolutional neural network for visual saliency prediction trained with...

DeepMovie
 Referenced in 1 article
[sw15171]
 DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies. A recent paper ... another image. First, they use convolutional neural network features to build a statistical model...