{overleaf template gallery}LaTeX templates and examples — Recent

Plantilla Repositorio de Matemáticas Escuela Colombiana de Ingeniería Julio Garavito

Lista de exercícios para disciplina de computação básica para física - Fortran na UFSM

Cheat sheet for Linear Algebra and Differential Equations

Basic template that can be used to format/write your MAP!

Template for the final assignment report for the course MV013 Statistics for Computer Science taught at the Faculy of Informatics, Masaryk University, Brno.

Sidebar CV template with font awesome icons.

Template for students completing reports for course ME5701 -''Proyectos en materiales y manufactura''- at University of Chile

The subfiles package and class can help with typesetting multi-file projects, where subsidiary files will inherit the main file's preamble when they themselves are compiled (i.e. "set as main" in Overleaf projects. Note, though, that at present .tex files inside a folder cannot be set as a project's main file.

Although the analysis of data is a task that has gained the interest of the statistical community in recent years and whose familiarity with the statistical computing environment, they encourage the current statistical community (to students and teachers of the area) to complete statistical analysis reproducible by means of the tool R. However for years there has been a gap between the calculation of matrices on a large scale and the term "big data", in this work the Normalized Cut algorithm for images is applied. Despite the expected, the R environment to do image analysis is poorly, in comparison with other computing platforms such as the Python language or with specialized software such as OpenCV. Being well known the absence of such function, in this work we share an implementation of the Normalized Cut algorithm in the R environment with extensions to programs and processes performed in C ++, to provide the user with a friendly interface in R to segment images. The article concludes by evaluating the current implementation and looking for ways to generalize the implementation for a large scale context and reuse the developed code. Key words: Normaliced Cut, image segmentation, Lanczos algorithm, eigenvalues and eigenvectors, graphs, similarity matrix, R (the statistical computing environment), open source, large scale and big data.