Skip to content

vsantjr/IDeepS

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Project IDeepS

The project Classificação de imagens e dados via redes neurais profundas para múltiplos domínios (Image and data classification via Deep neural networks for multiple domainS - IDeepS) is a continuation of a previous project and whose current objective is to propose recommendations/suggestions for the best deep neural network (DNN) models to be used for the remote sensing (which includes aerial images obtained by unmanned aerial vehicles (UAVs), airplanes, as well as images obtained by satellites), astrophysics, and health domains. Image classification will be the main computer vision task considered, but other tasks will be evaluated, also taking into account the greater diversity of distinct data.

The IDeepS project is supported by the Laboratório Nacional de Computação Científica (LNCC/MCTI, Brazil) via resources of the SDumont supercomputer. Researchers, professors and post-graduate students from the following organisations are involved in the project: Instituto Nacional de Pesquisas Espaciais (INPE), Instituto de Estudos Avançados (IEAv), Universidade Federal de São Paulo - Campus São José dos Campos (UNIFESP), Universidade Federal de São Carlos - Campus Sorocaba (UFSCar), and Universidade Estadual Paulista Júlio de Mesquita Filho - Campus Bauru (UNESP).

Publications

Team

Member Organisation
Álvaro Luiz Fazenda UNIFESP
Bruno Nardi de Carvalho Dantas ITA
Daniel Augusto de Sousa Mendes INPE
Eduardo Bouhid Neto UNIFESP
Elcio Hideiti Shiguemori IEAv
Hugo Resende UNIFESP
João Paulo Papa UNESP
Jurandy Gomes de Almeida Junior UFSCar
Marcelo Augusto Sudo UNIFESP
Mateus de Souza Miranda INPE
Nathan Augusto Zacarias Xavier ITA
Rafael Marinho de Andrade INPE
Reinaldo Roberto Rosa INPE
Samuel Felipe dos Santos UNIFESP
Thales Sehn Körting INPE
Valdivino Alexandre de Santiago Júnior (Coordinator) INPE

SDumont User Manual: Deep Learning

Directives and suggestions on how one can perform the setup and run deep learning (DL) applications in the SDumont supercomputer are presented here.

Author

Valdivino Alexandre de Santiago Júnior

Licence

This project is licensed under the GNU GENERAL PUBLIC LICENSE, Version 3 (GPLv3) - see the LICENSE.md file for details.

Cite

Please cite this repository if you use it as:

V. A. Santiago Júnior. Project IDeepS, 2024. Acessed on: date of access. Available at: https://github.com/vsantjr/IDeepS.

About

Project IDeepS: Image and data classification via Deep neural networks for multiple domainS

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published