• DeepTracker

  • Referenced in 3 articles [sw25889]
  • DeepTracker: Visualizing the Training Process of Convolutional Neural Networks. Deep convolutional neural networks (CNNs) have ... practically a trial-and-error process that consumes a tremendous amount of time and computer...
  • DeepVS

  • Referenced in 4 articles [sw16458]
  • atom contexts that is further processed by a convolutional layer. One of the main advantages...
  • TRINICON

  • Referenced in 2 articles [sw08750]
  • framework for multichannel blind signal processing for convolutive mixtures, such as blind source separation ... call TRINICON (Triple-N ICA for convolutive mixtures). Both, links to popular algorithms and several ... using multivariate spherically invariant random processes (SIRP) to efficiently model speech, and show...
  • convoSPAT

  • Referenced in 4 articles [sw15289]
  • Based Nonstationary Spatial Modeling. Fits convolution-based nonstationary Gaussian process models to point-referenced spatial...
  • DenseCap

  • Referenced in 5 articles [sw27203]
  • propose a Fully Convolutional Localization Network (FCLN) architecture that processes an image with a single ... optimization. The architecture is composed of a Convolutional Network, a novel dense localization layer...
  • QC-LDPC

  • Referenced in 9 articles [sw03246]
  • processing large circulant matrices. The Toom-Cook algorithm and the short Winograd convolution are considered...
  • fbfft

  • Referenced in 3 articles [sw25688]
  • NVIDIA Graphics Processing Units. We introduce two new Fast Fourier Transform convolution implementations: one based...
  • TorchIO

  • Referenced in 3 articles [sw32330]
  • NiBabel to efficiently process large 3D images during the training of convolutional neural networks...
  • APPLgrid

  • Referenced in 3 articles [sw18237]
  • calculation of any process where the hard subprocess weights from the convolution with...
  • V-Net

  • Referenced in 3 articles [sw35860]
  • Neural Networks for Volumetric Medical Image Segmentation. Convolutional Neural Networks (CNNs) have been recently employed ... popularity, most approaches are only able to process 2D images while most medical data used ... image segmentation based on a volumetric, fully convolutional, neural network. Our CNN is trained ... while requiring only a fraction of the processing time needed by other previous methods...
  • BayesNSGP

  • Referenced in 2 articles [sw30769]
  • closed-form, convolution-based covariance function with spatially-varying parameters; these parameter processes...
  • Count-ception

  • Referenced in 1 article [sw35861]
  • Fully Convolutional Redundant Counting. Counting objects in digital images is a process that should ... inside this frame. By processing the image in a fully convolutional way each pixel...
  • CAD2RL

  • Referenced in 1 article [sw35708]
  • flight, where a trial-and-error learning process is often impractical. In this paper ... represented by a deep convolutional neural network that directly processes raw monocular images and outputs...
  • ByteNet

  • Referenced in 2 articles [sw26537]
  • neural network for processing sequences. The ByteNet is a one-dimensional convolutional neural network that...
  • MT

  • Referenced in 2 articles [sw16854]
  • used to compute, both analytically and numerically, convolutions involving harmonic polylogarithms, polynomials or generalized functions ... Higgs boson production and the Drell–Yan process are discussed...
  • MeshCNN

  • Referenced in 2 articles [sw31207]
  • subsequent convolutions. MeshCNN learns which edges to collapse, thus forming a task-driven process where...
  • SEPLIB

  • Referenced in 2 articles [sw29224]
  • Parallel seismic data processing. In Geophysics measured seismic data sets need to be analyzed using ... operators consist of Fourier transforms, integral transforms, convolutions and other mathematical concepts. The result ... this paper we port a seismic processing package, called SEPLIB, which has been developed...
  • HEDSATS

  • Referenced in 1 article [sw29506]
  • manufacturing processes. The library constructs 3D solutions using one dimensional Green’s functions, convoluted ... electron beam, arc and friction stir welding processes. HEDSATS is released under the GNU Lesser...
  • iRNA-PseKNC

  • Referenced in 1 article [sw27658]
  • identify RNA 2’-O-methylation sites by convolution neural network and Chou’s pseudo components ... methylation transferase is involved in the process of 2’-O-methylation. In catalytic processes ... sites produce good results but these biochemical process and exploratory techniques are very expensive. Thus ... work, we proposed a simple and precise convolution neural network method namely: iRNA-PseKNC(2methyl...
  • SPORCO

  • Referenced in 3 articles [sw26283]
  • SPORCO: A Python package for standard and convolutional sparse representations. SParse Optimization Research COde (SPORCO ... miscellaneous support functions for signal and image processing with sparse representations. The sparse coding algorithms...