• 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 feed-forward networks such as Convolutional...
  • SegNet

  • Referenced in 4 articles [sw27575]
  • novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed ... engine consists of an encoder network, a corresponding decoder network followed by a pixel-wise ... 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 ... first-of-its-kind 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...
  • iRNA-PseKNC

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

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

  • Referenced in 2 articles [sw27213]
  • High-performance 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 time-invariant features, and bidirectional...
  • DeepSphere

  • Referenced in 1 article [sw29899]
  • DeepSphere: a spherical convolutional neural network. The code in this repository implements a generalization ... Convolutional Neural Networks (CNNs) to the sphere. We here model the discretised sphere ... graph of connected pixels. The resulting convolution is more efficient (especially when data doesn ... data at multiple scales. The graph neural network model is based on ChebNet...
  • Boda-RTC

  • 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 Loop-based 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 10-layer 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 one-dimensional 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...