Showing 5 open source projects for "convolution"

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  • 1
    ImageFiltering.jl

    ImageFiltering.jl

    Julia implementations of multidimensional array convolution

    Julia implementations of multidimensional array convolution and nonlinear stencil operations. ImageFiltering implements blurring, sharpening, gradient computation, and other linear filtering operations, as well nonlinear filters like min/max.
    Downloads: 2 This Week
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  • 2
    DSP.jl

    DSP.jl

    Filter design, periodograms, window functions

    DSP.jl provides a number of common digital signal processing routines in Julia.
    Downloads: 2 This Week
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  • 3
    DiffEqOperators.jl

    DiffEqOperators.jl

    Linear operators for discretizations of differential equations

    ...For the operators, both centered and upwind operators are provided, for domains of any dimension, arbitrarily spaced grids, and for any order of accuracy. The cases of 1, 2, and 3 dimensions with an evenly spaced grid are optimized with a convolution routine from NNlib.jl. Care is taken to give efficiency by avoiding unnecessary allocations, using purpose-built stencil compilers, allowing GPUs and parallelism, etc. Any operator can be concretized as an Array, a BandedMatrix or a sparse matrix.
    Downloads: 4 This Week
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  • 4
    AlphaPlot

    AlphaPlot

    Interactive scientific graphing and data analysis software.

    ...The spreadsheets as well as graphs and note windows are gathered in a project and can be organized using folders. The built-in analysis operations include column/row statistics, (de)convolution, FFT and FFT-based filters. Scripting Console support in-place evaluation of mathematical expressions and scrtipting interface to ECMAScript like dynamic scripting language(java script). The GUI of the application uses the Qt toolkit. Periodic test builds are available here http://alphaplot.sourceforge.net/test-build.html
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    Downloads: 43 This Week
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  • 5
    Deep Learning with PyTorch

    Deep Learning with PyTorch

    Latest techniques in deep learning and representation learning

    This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. To be able to follow the exercises, you are going to need a laptop with Miniconda (a...
    Downloads: 0 This Week
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