imageBless. When using theimguidedfilterfunction, you can control the value of ε, by tuning theDegreeOfSmoothingname-value argument, and the degree of influence of the neighborhood on the filtering, by specifying theNeighborhoodSizename-value argument. The neighborhood size is the radius of the ...
Linear filtering of an image is accomplished through an operation calledconvolution. Convolution is a neighborhood operation in which each output pixel is the weighted sum of neighboring input pixels. The matrix of weights is called theconvolution kernel, also known as thefilter. A convolution kernel...
HiSec Insight enables the capability of disabling code execution on memory pages to prevent buffer overflow vulnerabilities and enhance system security. The memory address randomization mechanism is enabled to randomize the layout of linear areas such as heaps, stacks, and shared library mappings. This...
What is hybrid topology? What is tree topology? What is a star topology? What is a bus topology? What is linear bus topology? What is the most common topology? What is ring topology in computer network? What is layered architecture?
To perform linear convolution with and , the lengths are and , giving . Using the matrix method, the output is . For circular convolution, both sequences must be the same length . Since has length and has length , we append a zero to ...
Virtual screeningis a computational technique used in drug discovery to evaluate large libraries of small molecules or compounds to identify potential drug candidates that can bind to a biological target, such as a protein. Virtual screening can complement traditional high-throughput screening in the qu...
An autoencoder for collaborative filtering learns a non-linear representation of a user-item matrix and reconstructs it by determining missing values. The NVIDIA GPU-accelerated Variational Autoencoder for Collaborative Filtering (VAE-CF) is an optimized implementation of the architecture first ...
Linear regressionpredicts the value of a variable based on the value of another variable. Nonlinear regression is used when an output isn't reproducible from linear inputs. With this, data points share a nonlinear relationship; for example, the data might have a nonlinear, curvy trend. ...
NPPIF, filtering and computer vision functions in nppi_filtering_functions.h, NPPIG, geometry transformation functions found in nppi_geometry_transforms.h, NPPIM, morphological operation functions found in nppi_morphological_operations.h, NPPIST, statistics and linear transform in nppi_statistics_func...
Each regression algorithm has a different ideal use case. For example, linear regression excels at predicting continuous outputs, while time series regression is best for forecasting future values. How does unsupervised machine learning work?