Zobrazeno 1 - 10
of 141
pro vyhledávání: '"Hemerson Pistori"'
Autor:
João Porto, Gabriel Higa, Vanessa Weber, Fabrício Weber, Newton Loebens, Pietro Claure, Leonardo de Almeida, Karla Porto, Hemerson Pistori
Publikováno v:
AgriEngineering, Vol 6, Iss 3, Pp 2941-2954 (2024)
This study explores the use of a Siamese neural network architecture to enhance classification performance in few-shot learning scenarios, with a focus on bovine facial recognition. Traditional methodologies often require large datasets, which can si
Externí odkaz:
https://doaj.org/article/fc5b313355314e5c94090257b3cc37a9
Autor:
Alexandre de Oliveira Bezerra, Vanessa Ap. de Moraes Weber, Fabricio de Lima Weber, Yasmin Alves de Arruda, Rodrigo da Costa Gomes, Gabriel Toshio Hirokawa Higa, Hemerson Pistori, Rodrigo Gonçalves Mateus
Publikováno v:
Smart Agricultural Technology, Vol 8, Iss , Pp 100489- (2024)
Assessing the phenotype of cattle through human visual inspection is a very common and important practice in precision cattle breeding. This paper presents the results of a correlation analysis between scores produced by humans for Nelore cattle and
Externí odkaz:
https://doaj.org/article/08937a8c01574b018a1fa6d4a3456054
Autor:
Diogo Nunes Gonçalves, José Marcato Junior, Mauro dos Santos de Arruda, Vanessa Jordão Marcato Fernandes, Ana Paula Marques Ramos, Danielle Elis Garcia Furuya, Lucas Prado Osco, Hongjie He, Lucio André de Castro Jorge, Jonathan Li, Farid Melgani, Hemerson Pistori, Wesley Nunes Gonçalves
Publikováno v:
Heliyon, Vol 10, Iss 11, Pp e31730- (2024)
Identifying plantation lines in aerial images of agricultural landscapes is re-quired for many automatic farming processes. Deep learning-based networks are among the most prominent methods to learn such patterns and extract this type of information
Externí odkaz:
https://doaj.org/article/0b48a64d1da542c2a75b433202b35452
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
Autor:
João Vitor de Andrade Porto, Arlinda Cantero Dorsa, Vanessa Aparecida de Moraes Weber, Karla Rejane de Andrade Porto, Hemerson Pistori
Publikováno v:
Smart Agricultural Technology, Vol 5, Iss , Pp 100307- (2023)
This paper examines the potential of using few-shot learning and computer vision techniques for detecting, identifying, and counting agricultural pests and diseases in images. A systematic review of papers published between 2020 and 2022 was conducte
Externí odkaz:
https://doaj.org/article/e9b563ec4d654964b719137a00049470
Autor:
Higor Henrique Picoli Nucci, Riquiette Gomes de Azevedo, Mylena Corrêa Nogueira, Celso Soares Costa, Denilson de Oliveira Guilherme, Gabriel Toshio Hirokawa Higa, Hemerson Pistori
Publikováno v:
Smart Agricultural Technology, Vol 5, Iss , Pp 100239- (2023)
Guavira is a Brazilian Cerrado's biome native fruit, from the Campomanesia spp. species, that generates income for small producers and indigenous people. Due to its seed's recalcitrant power, guavira is very difficult to produce on a large scale. Thi
Externí odkaz:
https://doaj.org/article/3883ff35676f4bc995af0cc761b7c5d2
Autor:
José Augusto Correa Martins, José Marcato Junior, Marlene Pätzig, Diego André Sant'Ana, Hemerson Pistori, Veraldo Liesenberg, Anette Eltner
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 9, Iss 1, Pp 1-16 (2023)
Abstract The use of uncrewed aerial vehicle to map the environment increased significantly in the last decade enabling a finer assessment of the land cover. However, creating accurate maps of the environment is still a complex and costly task. Deep l
Externí odkaz:
https://doaj.org/article/0e41ed331c154d7daa6b254e8de84dff
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
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
Autor:
Celso Soares Costa, Wesley Nunes Gonçalves, Vanda Alice Garcia Zanoni, Mauro dos Santos de Arruda, Mário de Araújo Carvalho, Edgar Nascimento, José Marcato Junior, Odair Diemer, Hemerson Pistori
Publikováno v:
Smart Agricultural Technology, Vol 4, Iss , Pp 100160- (2023)
In this work, we propose a new way for automatically counting fish larvae in Petri dishes using images captured by a standard smartphone. A new tilapia larvae image dataset for training and validating machine learning models has been created and used
Externí odkaz:
https://doaj.org/article/6954a2a9edcc41bf8610e3363c4b2728