Výsledky vyhledávání - "Gilberto Astolfi"

Akademický článek

YOLO performance analysis for real-time detection of soybean pests

Autor: Everton Castelão Tetila, Fábio Amaral Godoy da Silveira, Anderson Bessa da Costa, Willian Paraguassu Amorim, Gilberto Astolfi, Hemerson Pistori, Jayme Garcia Arnal Barbedo

Publikováno v: Smart Agricultural Technology, Vol 7, Iss , Pp 100405- (2024)

In this work, we evaluated the You Only Look Once (YOLO) architecture for real-time detection of soybean pests. We collected images of the soybean plantation in different days, locations and weather conditions, between the phenological stages R1 to R

Externí odkaz: https://doaj.org/article/1b792394beda4d15a2dca5fa7b3db2e6

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Akademický článek

Pseudo-label semi-supervised learning for soybean monitoring

Autor: Gabriel Kirsten Menezes, Gilberto Astolfi, José Augusto Correa Martins, Everton Castelão Tetila, Adair da Silva Oliveira Junior, Diogo Nunes Gonçalves, José Marcato Junior, Jonathan Andrade Silva, Jonathan Li, Wesley Nunes Gonçalves, Hemerson Pistori

Publikováno v: Smart Agricultural Technology, Vol 4, Iss , Pp 100216- (2023)

This paper presents a semi-supervised learning method based on superpixels and convolutional neural networks (CNNs) to assign and improve the identification of weeds in soybean crops. Despite its promising results, CNNs require massive amounts of lab

Externí odkaz: https://doaj.org/article/71e9ad13045d47a0b4f2f3fdbcf1cf74

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Akademický článek

Deep neural networks with attention mechanisms for Spodoptera frugiperda pupae sexing

Autor: João Vitor de Andrade Porto, Fabio Prestes Cesar Rezende, Higor Henrique Picoli Nucci, Antonia Railda Roel, Gilberto Astolfi, Hemerson Pistori

Publikováno v: Smart Agricultural Technology, Vol 4, Iss , Pp 100200- (2023)

The Spodoptera frugiperda caterpillar is an object of study of great importance to the national economy of Brazil since it directly attacks the cultivations of a diverse amount of agricultural products. Since the sexing of this insect is an arduous a

Externí odkaz: https://doaj.org/article/92229296ed0c4b1ab982e3cf89788f18

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Akademický článek

Fingerlings mass estimation: A comparison between deep and shallow learning algorithms

Autor: Adair da Silva Oliveira Junior, Diego André Sant’Ana, Marcio Carneiro Brito Pache, Vanir Garcia, Vanessa Aparecida de Moares Weber, Gilberto Astolfi, Fabricio de Lima Weber, Geazy Vilharva Menezes, Gabriel Kirsten Menezes, Pedro Lucas França Albuquerque, Celso Soares Costa, Eduardo Quirino Arguelho de Queiroz, João Victor Araújo Rozales, Milena Wolff Ferreira, Marco Hiroshi Naka, Hemerson Pistori

Publikováno v: Smart Agricultural Technology, Vol 1, Iss , Pp 100020- (2021)

The paper presents some results regarding the automatic mass estimation of Pintado Real fingerlings, using machine learning techniques to support the fish production process. For this purpose, an image dataset called FISHCV1206FSEG, was created which

Externí odkaz: https://doaj.org/article/6ba35f5a32c547899ff4f496b328e284

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Akademický článek

Recognizing and counting Dendrocephalus brasiliensis (Crustacea: Anostraca) cysts using deep learning.

Autor: Angelica Christina Melo Nunes Astolfi, Gilberto Astolfi, Maria Gabriela Alves Ferreira, Thaynara D'avalo Centurião, Leyzinara Zenteno Clemente, Bruno Leonardo Marques Castro de Oliveira, João Vitor de Andrade Porto, Kennedy Francis Roche, Edson Takashi Matsubara, Hemerson Pistori, Mayara Pereira Soares, William Marcos da Silva

Publikováno v: PLoS ONE, Vol 16, Iss 3, p e0248574 (2021)

The Dendrocephalus brasiliensis, a native species from South America, is a freshwater crustacean well explored in conservational and productive activities. Its main characteristics are its rusticity and resistance cysts production, in which the hatch

Externí odkaz: https://doaj.org/article/d382473853be48788e891667c905920f

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An approach for applying natural language processing to image classification problems

Autor: Gilberto Astolfi, Diego André Sant’Ana, João Vitor de Andrade Porto, Fábio Prestes Cesar Rezende, Everton Castelão Tetila, Edson Takashi Matsubara, Hemerson Pistori

Publikováno v: Neurocomputing. 513:372-382

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::669289408d9001f806bfad4265f9207a
https://doi.org/10.1016/j.neucom.2022.09.131

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Combining Syntactic Methods With LSTM to Classify Soybean Aerial Images

Autor: Nícolas Alessandro de Souza Belete, Vanessa Aparecida de Moares Weber, Marcio Carneiro Brito Pache, Geazy Vilharva Menezes, Gilberto Astolfi, Hemerson Pistori, Adair da Silva Oliveira Junior, Gabriel Menezes, Everton Castelão Tetila, Edson Takashi Matsubara

Publikováno v: IEEE Geoscience and Remote Sensing Letters. 18:2182-2186

Syntactic methods in computer vision represent visual patterns in a hierarchical and compositional perspective, which is converted to strings. Long short-term memory (LSTM) is able to learn patterns in sequences. In this letter, we propose a syntacti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ad413160f1dcba156e30ae7b05a95632
https://doi.org/10.1109/lgrs.2020.3014938

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Forensic palynology: computer vision and geotechnologies to support criminalistics expertise

Autor: Ariadne Barbosa Gonçalves, Pedro Lucas França Albuquerque, Rodolfo de França Alves, Gilberto Astolfi, Felipe Silveira Brito Borges, Milena dos Santos Carmona, Marney Pascoli Cereda, Sergio Augusto de Miranda Chaves, Alessandro dos Santos Ferreira, Raquel de Faria Godoi, Geazy Vilharva Menezes, Wedney Rodolpho de Oliveira, Antonio Conceição Paranhos Filho, Arnildo Pott, Karl Jan Reinhard, Francisco de Assis Ribeiro dos Santos, Hongbo Su, Hemerson Pistori

Publikováno v: Research, Society and Development; Vol. 11 No. 8; e31611830422
Research, Society and Development; Vol. 11 Núm. 8; e31611830422
Research, Society and Development; v. 11 n. 8; e31611830422
Research, Society and Development
Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI

Pollen grains can provide valuable information to forensic palynology, such as the time of death or the possible origin of a corpse. Forensic Palynology is a vital tool to be used in a criminal investigation because the different environment has dist

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78898211e1e5fc75b21f260831f68493
https://rsdjournal.org/index.php/rsd/article/view/30422

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A Deep-Learning Approach for Automatic Counting of Soybean Insect Pests

Autor: Geazy Vilharva Menezes, Bruno Brandoli Machado, Nícolas Alessandro de Souza Belete, Everton Castelão Tetila, Gilberto Astolfi, Hemerson Pistori

Publikováno v: IEEE Geoscience and Remote Sensing Letters. 17:1837-1841

The occurrence of insect pest attacks in soybean fields has worried farmers around the world. Early and automatic diagnosis of insect pests number could assess the infestation level of each plantation area to optimize the applications of pesticides i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::116e50912831dfb929613ffb6aa49986
https://doi.org/10.1109/lgrs.2019.2954735

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