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THz and thermal video data set This multispectral data set includes terahertz, thermal, visual, near infrared, and three-dimensional videos of objects hidden under people's clothes. 3D lookup tables are provided that allow you to project images onto 3D point clouds. More than 20 videos.
5 data sets that center around robotic failure to execute common tasks. Integer valued features such as torque and other sensor measurements. 463 Text Classification 1999 [206] L. Seabra et al. Pittsburgh Bridges Dataset Design description is given in terms of several properties of various bridges. Various bridge features are given. 108 Text
English: Printable pdf version of C Programming Wikibook. This file was created with MediaWiki to LaTeX . The LaTeX source code is attached to the PDF file (see imprint).
MATLAB (an abbreviation of "MATrix LABoratory" [22]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
A numerical modeling environment with a declarative and visual programming language based on influence diagrams. Ch: SoftIntegration 1 October 2001: 7.5.1 2 December 2015: $399 (commercial), $199 (academic), Free (student) Proprietary: C/C++ based numerical computing and graphical plotting [1] DADiSP: DSP Development 1984 1987 6.7 B02 17 ...
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Functionality similar to MATLAB and Octave. LAPACK++, a C++ wrapper library for LAPACK and BLAS; MFEM is a free, lightweight, scalable C++ library for finite element methods. Intel MKL, Intel Math Kernel Library (in C and C++), a library of optimized math routines for science, engineering, and financial applications, written in C/C++ and ...
Take a face category and a car category for an example. The face category may emphasize the codewords which represent "nose", "eye" and "mouth", while the car category may emphasize the codewords which represent "wheel" and "window". Given a collection of training examples, the classifier learns different distributions for different categories.