Pinned Repositories
Corona
dibd20.github.io
endnote
genpost
post generator
hugo-universal-theme
Port of the Universal theme to Hugo
Landsat-Classification-Using-Convolution-Neural-Network
Source code and files mentioned in the medium post titled "Is CNN equally shiny on mid-resolution satellite data?" available at https://towardsdatascience.com/is-cnn-equally-shiny-on-mid-resolution-satellite-data-9e24e68f0c08
mappe_italia_COVID19
Mappe che descrivono l'evoluzione dell'epidemia di COVID-19 in Italia
Python-CommonCode
Python-Practical-Application-on-Climate-Variability-Studies
This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.
QGIS-Plugin-Produce-Training-Samples-For-Deep-Learning
gouxiaoyun123's Repositories
gouxiaoyun123/Corona
gouxiaoyun123/dibd20.github.io
gouxiaoyun123/endnote
gouxiaoyun123/genpost
post generator
gouxiaoyun123/hugo-universal-theme
Port of the Universal theme to Hugo
gouxiaoyun123/Landsat-Classification-Using-Convolution-Neural-Network
Source code and files mentioned in the medium post titled "Is CNN equally shiny on mid-resolution satellite data?" available at https://towardsdatascience.com/is-cnn-equally-shiny-on-mid-resolution-satellite-data-9e24e68f0c08
gouxiaoyun123/mappe_italia_COVID19
Mappe che descrivono l'evoluzione dell'epidemia di COVID-19 in Italia
gouxiaoyun123/Python-CommonCode
gouxiaoyun123/Python-Practical-Application-on-Climate-Variability-Studies
This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.
gouxiaoyun123/QGIS-Plugin-Produce-Training-Samples-For-Deep-Learning
gouxiaoyun123/rinto1.github.io