• TorchIO

  • Referenced in 3 articles [sw32330]
  • images during the training of convolutional neural networks. We provide multiple generic as well...
  • ckn_kernel

  • Referenced in 5 articles [sw31148]
  • here, here, here) and neural tangent kernels for convolutional networks (NTK or CNTK, see here...
  • MeshCNN

  • Referenced in 2 articles [sw31207]
  • inhibits mesh analysis efforts using neural networks that combine convolution and pooling operations. In this ... shapes using MeshCNN, a convolutional neural network designed specifically for triangular meshes. Analogous to classic...
  • MidiNet

  • Referenced in 2 articles [sw36061]
  • Convolutional Generative Adversarial Network for Symbolic-domain Music Generation. Most existing neural network models ... model proposed by DeepMind shows that convolutional neural networks (CNNs) can also generate realistic musical...
  • ByteNet

  • Referenced in 2 articles [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...
  • 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...
  • Cubical Ripser

  • Referenced in 2 articles [sw35623]
  • analysis in which persistent homology and convolutional neural networks are successfully combined. Our open-source...
  • HCP

  • Referenced in 2 articles [sw28402]
  • Framework for Multi-Label Image Classification. Convolutional Neural Network (CNN) has demonstrated promising performance...
  • ArcFace

  • Referenced in 2 articles [sw33958]
  • challenges in feature learning using Deep Convolutional Neural Networks (DCNNs) for large-scale face recognition...
  • Semantic3D.net

  • Referenced in 2 articles [sw36654]
  • benchmark that use deep convolutional neural networks (CNNs) as a work horse, which already show...
  • DeepSleepNet

  • Referenced in 2 articles [sw21053]
  • proposed model, we utilize Convolutional Neural Networks (CNNs) to extract time-invariant features, and bidirectional...
  • FeatureVis

  • Referenced in 1 article [sw15650]
  • Library for Visualizing Learned Features in Convolutional Neural Networks. Over the last decade, Convolutional Neural...
  • 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...
  • DHSNet

  • Referenced in 1 article [sw36673]
  • hierarchical saliency network (DHSNet) based on convolutional neural networks for detecting salient objects. DHSNet first ... combination. Then a novel hierarchical recurrent convolutional neural network (HRCNN) is adopted to further hierarchically...
  • SqueezeDet

  • Referenced in 1 article [sw32551]
  • SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection ... work, we propose SqueezeDet, a fully convolutional neural network for object detection that aims ... above constraints. In our network, we use convolutional layers not only to extract feature maps ... neural network, thus it is extremely fast. Our model is fully-convolutional, which leads...
  • 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...
  • MgNet

  • Referenced in 1 article [sw35862]
  • unified framework of multigrid and convolutional neural network. We develop a unified model, known ... MgNet, that simultaneously recovers some convolutional neural networks (CNN) for image classification and multigrid ... unified model, the function of various convolution operations and pooling used...
  • Conformer

  • Referenced in 1 article [sw35794]
  • Speech Recognition. Recently Transformer and Convolution neural network (CNN) based models have shown promising results ... Automatic Speech Recognition (ASR), outperforming Recurrent neural networks (RNNs). Transformer models are good at capturing ... worlds by studying how to combine convolution neural networks and transformers to model both local ... this regard, we propose the convolution-augmented transformer for speech recognition, named Conformer. Conformer significantly...