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MathWorks Inc 2016a
2016a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 407 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/2016a+parallel+computing+toolbox+mathworks/Computer+Vision+Toolbox/pmc06997898-85-7-8
Average 96 stars, based on 407 article reviews
2016a - by Bioz Stars, 2026-10
96/100 stars

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Article Title: Optical Smart-Wheel Sensing of Tire Deformation for Tire State and Load Estimation.
Article Snippet: The Camera Calibrator app in MATLAB R2025b (Computer Vision Toolbox, version 25.2) was used with checkerboard images acquired at different positions and orientations.

Article Title: Dynamic modulation of social gaze by sex and familiarity in marmoset dyads
Article Snippet: The corners of the checkerboard were automatically detected via a standard algorithm (detectCheckerboardPoints() function in the Image Processing and Computer Vision toolbox in MATLAB).

Article Title: A Novel Image Inpainting Approach for Geometric Calibration of Low-Cost Handheld Thermal Cameras.
Article Snippet: Following preprocessing, geometric calibration was performed using Zhang’s method [22] under a pinhole camera model, implemented in MATLAB R2025b using routines from the Computer Vision Toolbox.

Article Title: Dynamic modulation of social gaze by sex and familiarity in marmoset dyads
Article Snippet: The intrinsic parameters of each camera were estimated based on the data obtained from the checkerboard corner detection algorithm (estimateCameraParameters() function in Image Processing and Computer Vision toolbox in MATLAB).

Software:

Article Title: Contextual camera controls during a collaboration session in a heterogenous computing platform
Article Snippet: .. Non-limiting examples of available AI algorithms, software, and libraries that may be utilized within embodiments of systems and methods described herein include, but are not limited to: PYTHON, OPENCV, INCEPTION, THEANO, TORCH, PYTORCH, PYLEARN2, NUMPY, BLOCKS, TENSORFLOW, MXNET, CAFFE, LASAGNE, KERAS, CHAINER, MATLAB Deep Learning, CNTK, MatConvNet (a MATLAB toolbox implementing convolutional neural networks for computer vision applications), DeepLearnToolbox (a Matlab toolbox for Deep Learning from Rasmus Berg Palm), BigDL, Cuda-Convnet (a fast C++/CUDA implementation of convolutional or feed-forward neural networks), Deep Belief Networks, RNNLM, RNNLIB-RNNLIB, matrbm, deeplearning4j, Eblearn.Ish, deepmat, MShadow, Matplotlib, SciPy, CXXNET, Nengo-Nengo, Eblearn, cudamat, Gnumpy, 3-way factored RBM and mcRBM, mPoT, ConvNet, ELEKTRONN, OpenNN, NEURALDESIGNER, Theano Generalized Hebbian Learning, Apache SINGA, Lightnet, and SimpleDNN. ..

Article Title: Systems and methods for connecting a conference room to an ongoing meeting session
Article Snippet: Such AI/ML model(s) may implement: a neural network (e.g., artificial neural network, deep neural network, convolutional neural network, recurrent neural network, autoencoders, reinforcement learning, etc.), fuzzy logic, deep learning, deep structured learning hierarchical learning, Support Vector Machine (SVM) (e.g., linear SVM, nonlinear SVM, SVM regression, etc.), decision tree learning (e.g., classification and regression tree or “CART”), Very Fast Decision Tree (VFDT), ensemble methods (e.g., ensemble learning, Random Forests, Bagging and Pasting, Patches and Subspaces, Boosting, Stacking, etc.), dimensionality reduction (e.g., Projection, Manifold Learning, Principal Components Analysis, etc.), or the like. .. Non-limiting examples of available AI/ML algorithms, models, software, and libraries that may be utilized within embodiments of systems and methods described herein include, but are not limited to: PYTHON, OPENCV, INCEPTION, THEANO, TORCH, PYTORCH, PYLEARN2, NUMPY, BLOCKS, TENSORFLOW, MXNET, CAFFE, LASAGNE, KERAS, CHAINER, MATLAB Deep Learning, CNTK, MatConvNet (a MATLAB toolbox implementing convolutional neural networks for computer vision applications), DeepLearnToolbox (a Matlab toolbox for Deep Learning from Rasmus Berg Palm), BigDL, Cuda-Convnet (a fast C++/CUDA implementation of convolutional or feed-forward neural networks), Deep Belief Networks, RNNLM, RNNLIB-RNNLIB, matrbm, deeplearning4j, Eblearn.lsh, deepmat, MShadow, Matplotlib, SciPy, CXXNET, Nengo-Nengo, Eblearn, cudamat, Gnumpy, 3-way factored RBM and mcRBM, mPOT, ConvNet, ELEKTRONN, OpenNN, NEURALDESIGNER, Theano Generalized Hebbian Learning, Apache SINGA, Lightnet, and SimpleDNN. ..

Article Title: Systems and methods for remotely provisioning facial recognition data to heterogeneous computing platforms
Article Snippet: .. Non-limiting examples of software and libraries which may be utilized within embodiments of systems and methods described herein to perform AI modeling operations include, but are not limited to: PYTHON, OPENCV, scikit-learn, INCEPTION, THEANO, TORCH, PYTORCH, PYLEARN2, NUMPY, BLOCKS, TENSORFLOW, MXNET, CAFFE, LASAGNE, KERAS, CHAINER, MATLAB Deep Learning, CNTK, MatConvNet (a MATLAB toolbox implementing convolutional neural networks for computer vision applications), DeepLearnToolbox (a Matlab toolbox for Deep Learning from Rasmus Berg Palm), BigDL, Cuda-Convnet (a fast C++/CUDA implementation of convolutional or feed-forward neural networks), Deep Belief Networks, RNNLM, RNNLIB-RNNLIB, matrbm, deeplearning4j, Eblearn.lsh, deepmat, MShadow, Matplotlib, SciPy, CXXNET, Nengo-Nengo, Eblearn, cudamat, Gnumpy, 3-way factored RBM and mcRBM, mPoT, ConvNet, ELEKTRONN, OpenNN, NEURALDESIGNER, Theano Generalized Hebbian Learning, Apache SINGA, Lightnet, and SimpleDNN. ..



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MathWorks Inc 2016a parallel computing toolbox mathworks
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2016a Parallel Computing Toolbox Mathworks, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/2016a+parallel+computing+toolbox+mathworks/Parallel+Computing+Toolbox/pmc05568912-1273-33-36
Average 95 stars, based on 1 article reviews
2016a parallel computing toolbox mathworks - by Bioz Stars, 2026-10
95/100 stars
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Journal: Neuron

Article Title: A neural signature of divisive normalization at the level of multisensory integration in primate cortex

doi: 10.1016/j.neuron.2017.06.043

Figure Lengend Snippet: Key Resources Table

Article Snippet: ​ Reagent or Resource Source Identifier Experimental Models: Organisms/Strains Macaca mulatta Primate Products N/A Software and Algorithms MATLAB 2016a statistics and machine learning toolbox Mathworks https://www.mathworks.com MATLAB 2016a optimization toolbox Mathworks https://www.mathworks.com MATLAB 2016a parallel-computing toolbox Mathworks https://www.mathworks.com MATLAB model simulation code This paper N/A TEMPO Experiment control system Reflective computing http://reflectivecomputing.com/ Visual stimulus generation code, written in Visual C++ using the OpenGL graphics libraries This paper; Gu et al. 2006 N/A Other Tungsten microelectrodes, Epoxylite insulated Frederic Haer Company https://www.fh-co.com MOOG 6DOF2000E, 6-degree-of-freedom motion platform Moog, Inc http://www.moog.com Christie Mirage S + 3K, digital light projector Christie Digital www.christiedigital.com Open in a separate window Key Resources Table Many neurons in macaque area MSTd show a specific form of cross-modal suppression Cross-modal suppression is predicted by a divisive normalization mechanism Neurons in area MT, which project to MSTd, do not show cross-modal suppression Multisensory integration in area MSTd likely involves divisive normalization

Techniques: Software