• CNN-RNN

  • Referenced in 8 articles [sw28401]
  • Multi-label Image Classification. While deep convolutional neural networks (CNNs) have shown a great success...
  • AI2

  • Referenced in 4 articles [sw40547]
  • robustness) of realistic neural networks (e.g., convolutional neural networks). The key insight behind ... reasoning about safety and robustness of neural networks in terms of classic abstract interpretation, enabling ... behavior of fully connected and convolutional neural network layers with rectified linear unit activations (ReLU ... state-of-the-art defenses for neural networks, (iii) AI 2 is significantly faster than...
  • SYNTHIA Dataset

  • Referenced in 7 articles [sw35060]
  • driving. Recent revolutionary results of deep convolutional neural networks (DCNNs) foreshadow the advent of reliable...
  • SqueezeDet

  • Referenced in 4 articles [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...
  • BOHB

  • Referenced in 5 articles [sw35481]
  • neural networks, deep reinforcement learning, and convolutional neural networks. Our method is robust and versatile...
  • Conformer

  • Referenced in 4 articles [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...
  • VGGFace2

  • Referenced in 6 articles [sw38590]
  • without Squeeze-and-Excitation blocks) Convolutional Neural Networks on VGGFace2, on MS- Celeb...
  • MemNet

  • Referenced in 5 articles [sw38076]
  • Image Restoration. Recently, very deep convolutional neural networks (CNNs) have been attracting considerable attention...
  • rocket

  • Referenced in 5 articles [sw38157]
  • Building on the recent success of convolutional neural networks for time series classification, we show...
  • CayleyNets

  • Referenced in 5 articles [sw38090]
  • CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters. The rise of graph-structured ... such as social networks, regulatory networks, citation graphs, and functional brain networks, in combination with ... paper, we introduce a new spectral domain convolutional architecture for deep learning on graphs...
  • SyncSpecCnn

  • Referenced in 5 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...
  • MeshCNN

  • Referenced in 4 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...
  • CosFace

  • Referenced in 5 articles [sw39109]
  • owing to the advancement of deep convolutional neural networks (CNNs). The central task of face...
  • ArcFace

  • Referenced in 5 articles [sw33958]
  • challenges in feature learning using Deep Convolutional Neural Networks (DCNNs) for large-scale face recognition...
  • CovXNet

  • Referenced in 3 articles [sw41860]
  • CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection ... chest X-rays. A deep convolutional neural network (CNN) based architecture, named as CovXNet...
  • SuperCNN

  • Referenced in 3 articles [sw36672]
  • SuperCNN: A Superpixelwise Convolutional Neural Network for Salient Object Detection. Existing computational models for salient ... deep learning techniques. A novel superpixelwise convolutional neural network approach, called SuperCNN, is proposed ... efficient manner. In contrast to the classical convolutional networks, SuperCNN has four main properties. First...
  • COVID-CAPS

  • Referenced in 4 articles [sw41861]
  • based diagnosis solutions, mainly based on Convolutional Neural Networks (CNNs), to facilitate identification of positive...
  • JigsawNet

  • Referenced in 3 articles [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...
  • COVID-Net

  • Referenced in 3 articles [sw41186]
  • COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases ... introduce COVID-Net, a deep convolutional neural network design tailored for the detection of COVID...
  • ByteNet

  • Referenced in 4 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...