Zobrazeno 1 - 10
of 124
pro vyhledávání: '"Goncalves, Wesley Nunes"'
Autor:
Osco, Lucas Prado, Wu, Qiusheng, de Lemos, Eduardo Lopes, Gonçalves, Wesley Nunes, Ramos, Ana Paula Marques, Li, Jonathan, Junior, José Marcato
Segmentation is an essential step for remote sensing image processing. This study aims to advance the application of the Segment Anything Model (SAM), an innovative image segmentation model by Meta AI, in the field of remote sensing image analysis. S
Externí odkaz:
http://arxiv.org/abs/2306.16623
Autor:
Goncalves, Diogo Nunes, Junior, Jose Marcato, Zamboni, Pedro, Pistori, Hemerson, Li, Jonathan, Nogueira, Keiller, Goncalves, Wesley Nunes
Multi-task learning has proven to be effective in improving the performance of correlated tasks. Most of the existing methods use a backbone to extract initial features with independent branches for each task, and the exchange of information between
Externí odkaz:
http://arxiv.org/abs/2305.02813
Autor:
Osco, Lucas Prado, de Lemos, Eduardo Lopes, Gonçalves, Wesley Nunes, Ramos, Ana Paula Marques, Junior, José Marcato
Recent advancements in Natural Language Processing (NLP), particularly in Large Language Models (LLMs), associated with deep learning-based computer vision techniques, have shown substantial potential for automating a variety of tasks. One notable mo
Externí odkaz:
http://arxiv.org/abs/2304.13009
Autor:
Gonçalves, Diogo Nunes, Junior, José Marcato, Arruda, Mauro dos Santos de, Fernandes, Vanessa Jordão Marcato, Ramos, Ana Paula Marques, Furuya, Danielle Elis Garcia, Osco, Lucas Prado, He, Hongjie, Jorge, Lucio André de Castro, Li, Jonathan, Melgani, Farid, Pistori, Hemerson, Gonçalves, Wesley Nunes
Publikováno v:
In Heliyon 15 June 2024 10(11)
Autor:
Bressan, Patrik Olã, Junior, José Marcato, Martins, José Augusto Correa, Gonçalves, Diogo Nunes, Freitas, Daniel Matte, Osco, Lucas Prado, Silva, Jonathan de Andrade, Luo, Zhipeng, Li, Jonathan, Garcia, Raymundo Cordero, Gonçalves, Wesley Nunes
Publikováno v:
International Journal of Applied Earth Observation and Geoinformation, 2022
Recently, methods based on Convolutional Neural Networks (CNN) achieved impressive success in semantic segmentation tasks. However, challenges such as the class imbalance and the uncertainty in the pixel-labeling process are not completely addressed.
Externí odkaz:
http://arxiv.org/abs/2102.04566
Autor:
de Arruda, Mauro dos Santos, Osco, Lucas Prado, Acosta, Plabiany Rodrigo, Gonçalves, Diogo Nunes, Junior, José Marcato, Ramos, Ana Paula Marques, Matsubara, Edson Takashi, Luo, Zhipeng, Li, Jonathan, Silva, Jonathan de Andrade, Gonçalves, Wesley Nunes
Publikováno v:
Expert Systems with Applications, 2022
This paper presents a Convolutional Neural Network (CNN) approach for counting and locating objects in high-density imagery. To the best of our knowledge, this is the first object counting and locating method based on a feature map enhancement and a
Externí odkaz:
http://arxiv.org/abs/2102.04366
Autor:
Gonçalves, Diogo Nunes, de Arruda, Mauro dos Santos, Pistori, Hemerson, Fernandes, Vanessa Jordão Marcato, Ramos, Ana Paula Marques, Furuya, Danielle Elis Garcia, Osco, Lucas Prado, He, Hongjie, Li, Jonathan, Junior, José Marcato, Gonçalves, Wesley Nunes
Deep learning-based networks are among the most prominent methods to learn linear patterns and extract this type of information from diverse imagery conditions. Here, we propose a deep learning approach based on graphs to detect plantation lines in U
Externí odkaz:
http://arxiv.org/abs/2102.03213
Autor:
Osco, Lucas Prado, Junior, José Marcato, Ramos, Ana Paula Marques, Jorge, Lúcio André de Castro, Fatholahi, Sarah Narges, Silva, Jonathan de Andrade, Matsubara, Edson Takashi, Pistori, Hemerson, Gonçalves, Wesley Nunes, Li, Jonathan
Publikováno v:
International Journal of Applied Earth Observation and Geoinformation, 2022
Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, surveys an
Externí odkaz:
http://arxiv.org/abs/2101.10861
Autor:
Osco, Lucas Prado, de Arruda, Mauro dos Santos, Gonçalves, Diogo Nunes, Dias, Alexandre, Batistoti, Juliana, de Souza, Mauricio, Gomes, Felipe David Georges, Ramos, Ana Paula Marques, Jorge, Lúcio André de Castro, Liesenberg, Veraldo, Li, Jonathan, Ma, Lingfei, Junior, José Marcato, Gonçalves, Wesley Nunes
Publikováno v:
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 174 (2021) 1-17
In this paper, we propose a novel deep learning method based on a Convolutional Neural Network (CNN) that simultaneously detects and geolocates plantation-rows while counting its plants considering highly-dense plantation configurations. The experime
Externí odkaz:
http://arxiv.org/abs/2012.15827
Publikováno v:
In Expert Systems With Applications 15 October 2023 228