Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Anesmar Olino de Albuquerque"'
Autor:
Osmar Luiz Ferreira de Carvalho, Osmar Abilio de Carvalho Junior, Anesmar Olino de Albuquerque, Nickolas Castro Santana, Renato Fontes Guimaraes, Roberto Arnaldo Trancoso Gomes, Dibio Leandro Borges
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 3403-3420 (2022)
Vehicle classification is a hot computer vision topic, with studies ranging from ground-view to top-view imagery. Top-view images allow understanding city patterns, traffic management, among others. However, there are some difficulties for pixel-wise
Externí odkaz:
https://doaj.org/article/f52dfe998e1745539dac392af1d6f9ce
Autor:
Osmar Luiz Ferreira de Carvalho, Osmar Abílio de Carvalho Júnior, Anesmar Olino de Albuquerque, Nickolas Castro Santana, Díbio Leandro Borges, Argelica Saiaka Luiz, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 112, Iss , Pp 102910- (2022)
Panoptic segmentation is a recent and powerful task that tackles individual object recognition (“things”) and multiple backgrounds (“stuff”) simultaneously. Remote sensing studies with panoptic segmentation are still restricted and recent, wi
Externí odkaz:
https://doaj.org/article/9280f8099fcd4b8b8b7eb9bfa0647a38
Autor:
Anesmar Olino de Albuquerque, Osmar Luiz Ferreira de Carvalho, Cristiano Rosa e Silva, Argelica Saiaka Luiz, Pablo P. de Bem, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimaraes, Osmar Abilio de Carvalho Junior
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 8447-8457 (2021)
The automatic detection of Center Pivot Irrigation Systems (CPIS) is fundamental for establishing public policies, especially in countries with a growth perspective in this technology, like Brazil. Previous studies to detect CPIS using deep learning
Externí odkaz:
https://doaj.org/article/f720753769e14802a5f818c9db6a786f
Autor:
Osmar Luiz Ferreira de Carvalho, Osmar Abílio de Carvalho Junior, Anesmar Olino de Albuquerque, Alex Gois Orlandi, Issao Hirata, Díbio Leandro Borges, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães
Publikováno v:
Remote Sensing, Vol 15, Iss 5, p 1240 (2023)
Wind energy is one of Brazil’s most promising energy sources, and the rapid growth of wind plants has increased the need for accurate and efficient inspection methods. The current onsite visits, which are laborious and costly, have become unsustain
Externí odkaz:
https://doaj.org/article/b272b9dde64c4b6aba5348a84cd911ad
Autor:
Ivo Augusto Lopes Magalhães, Osmar Abílio de Carvalho Júnior, Osmar Luiz Ferreira de Carvalho, Anesmar Olino de Albuquerque, Potira Meirelles Hermuche, Éder Renato Merino, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães
Publikováno v:
Remote Sensing, Vol 14, Iss 19, p 4858 (2022)
The state of Amapá within the Amazon biome has a high complexity of ecosystems formed by forests, savannas, seasonally flooded vegetation, mangroves, and different land uses. The present research aimed to map the vegetation from the phenological beh
Externí odkaz:
https://doaj.org/article/d859b3e4b390474fa7255e519219ecba
Autor:
Osmar Luiz Ferreira de Carvalho, Osmar Abílio de Carvalho Júnior, Cristiano Rosa e Silva, Anesmar Olino de Albuquerque, Nickolas Castro Santana, Dibio Leandro Borges, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães
Publikováno v:
Remote Sensing, Vol 14, Iss 4, p 965 (2022)
Panoptic segmentation combines instance and semantic predictions, allowing the detection of countable objects and different backgrounds simultaneously. Effectively approaching panoptic segmentation in remotely sensed data is very promising since it p
Externí odkaz:
https://doaj.org/article/a598fc48aeb14fdd8b30e251f695079e
Autor:
Osmar Luiz Ferreira de Carvalho, Rebeca dos Santos de Moura, Anesmar Olino de Albuquerque, Pablo Pozzobon de Bem, Rubens de Castro Pereira, Li Weigang, Dibio Leandro Borges, Renato Fontes Guimarães, Roberto Arnaldo Trancoso Gomes, Osmar Abílio de Carvalho Júnior
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 10, Iss 12, p 813 (2021)
Misappropriation of public lands is an ongoing government concern. In Brazil, the beach zone is public property, but many private establishments use it for economic purposes, requiring constant inspection. Among the undue targets, the individual mapp
Externí odkaz:
https://doaj.org/article/1cfaf34030df46ac9a40c1a4970318cf
Autor:
Marcus Vinícius Coelho Vieira da Costa, Osmar Luiz Ferreira de Carvalho, Alex Gois Orlandi, Issao Hirata, Anesmar Olino de Albuquerque, Felipe Vilarinho e Silva, Renato Fontes Guimarães, Roberto Arnaldo Trancoso Gomes, Osmar Abílio de Carvalho Júnior
Publikováno v:
Energies, Vol 14, Iss 10, p 2960 (2021)
Brazil is a tropical country with continental dimensions and abundant solar resources that are still underutilized. However, solar energy is one of the most promising renewable sources in the country. The proper inspection of Photovoltaic (PV) solar
Externí odkaz:
https://doaj.org/article/a8b0469d15fd457aad3078a4ae292d0c
Autor:
Osmar Luiz Ferreira de Carvalho, Osmar Abílio de Carvalho Júnior, Anesmar Olino de Albuquerque, Pablo Pozzobon de Bem, Cristiano Rosa Silva, Pedro Henrique Guimarães Ferreira, Rebeca dos Santos de Moura, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães, Díbio Leandro Borges
Publikováno v:
Remote Sensing, Vol 13, Iss 1, p 39 (2020)
Instance segmentation is the state-of-the-art in object detection, and there are numerous applications in remote sensing data where these algorithms can produce significant results. Nevertheless, one of the main problems is that most algorithms use R
Externí odkaz:
https://doaj.org/article/dc454eb05a884721948cd089e12292af
Autor:
Hugo Crisóstomo de Castro Filho, Osmar Abílio de Carvalho Júnior, Osmar Luiz Ferreira de Carvalho, Pablo Pozzobon de Bem, Rebeca dos Santos de Moura, Anesmar Olino de Albuquerque, Cristiano Rosa Silva, Pedro Henrique Guimarães Ferreira, Renato Fontes Guimarães, Roberto Arnaldo Trancoso Gomes
Publikováno v:
Remote Sensing, Vol 12, Iss 16, p 2655 (2020)
The Synthetic Aperture Radar (SAR) time series allows describing the rice phenological cycle by the backscattering time signature. Therefore, the advent of the Copernicus Sentinel-1 program expands studies of radar data (C-band) for rice monitoring a
Externí odkaz:
https://doaj.org/article/13874cb20b544ee690b441192fea9317