fabricio de lima weber

@portal.ufgd.edu.br

PG Zootecnia, mestrado e doutorado, área de concentração: Produção Animal
UNIVERSIDADE FEDERAL DA GRANDE DOURADOS - UFGD

fabricio de lima weber


               Download Compact PDF  
https://researchid.co/flweber

RESEARCH, TEACHING, or OTHER INTERESTS

Animal Science and Zoology, Computer Vision and Pattern Recognition, Artificial Intelligence
9

Scopus Publications

314

Scholar Citations

6

Scholar h-index

5

Scholar i10-index

Scopus Publications

  • A New Siamese Network Loss for Cattle Facial Recognition in a Few-Shot Learning Scenario
    João Porto, Gabriel Higa, Vanessa Weber, Fabrício Weber, Newton Loebens, Pietro Claure, Leonardo de Almeida, Karla Porto, Hemerson Pistori
    Agriengineering, 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 significantly stress animals during data collection. In contrast, the proposed method aims to reduce the number of images needed, thereby minimizing animal stress. Systematic experiments conducted on datasets representing both full and few-shot learning scenarios revealed that the Siamese network consistently outperforms traditional models, such as ResNet101. It achieved notable improvements, with mean values increasing by over 6.5% and standard deviations decreasing by at least 0.010 compared to the ResNet101 baseline. These results highlight the Siamese network’s robustness and consistency, even in resource-constrained environments, and suggest that it offers a promising solution for enhancing model performance with fewer data and reduced animal stress, despite its slower training speed.
  • Exploring cluster analysis in Nelore cattle visual score attribution
    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
    Smart Agricultural Technology, 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 a variety of measurements that can be derived from images or other instruments. It also presents a study using the k-means algorithm to generate new ways of clustering a batch of cattle using the measurements that most correlate with the animal's body weight and visual scores.
  • Counting cattle in UAV images using convolutional neural network
    Fabricio de Lima Weber, Vanessa Aparecida de Moraes Weber, Pedro Henrique de Moraes, Edson Takashi Matsubara, Débora Maria Barroso Paiva, Marina de Nadai Bonin Gomes, Luiz Orcírio Fialho de Oliveira, Sérgio Raposo de Medeiros, Maria Istela Cagnin
    Remote Sensing Applications Society and Environment, 2023
  • Fingerlings mass estimation: A comparison between deep and shallow learning algorithms
    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
    Smart Agricultural Technology, 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 is composed of 1206 images of fingerlings with their respective annotated masses. Through the fish contours, the area and perimeter were extracted, and submitted to the J48, SVM, and KNN classification algorithms and a linear regression algorithm. The images were also submitted to ResNet50, InceptionV3, Exception, VGG16, and VGG19 convolutional neural networks. As a result, the classification algorithm J48 reached an accuracy of 58.2% and a linear regression model capable of predicting the mass of a Pintado Real fingerling with a mean squared error of 1.5 g. The convolutional neural network ResNet50 obtained an accuracy of 67.08%. We can highlight the contributions of this work through the presentation of a methodology to classify the mass of fingerlings in a non-invasive way and by the analyses and comparing results of different machine learning algorithms for classification and regression.
  • Cattle weight estimation using active contour models and regression trees Bagging
    Vanessa Aparecida Moraes Weber, Fabricio de Lima Weber, Adair da Silva Oliveira, Gilberto Astolfi, Geazy Vilharva Menezes, João Vitor de Andrade Porto, Fábio Prestes Cesar Rezende, Pedro Henrique de Moraes, Edson Takashi Matsubara, Rodrigo Gonçalves Mateus, Thiago Luís Alves Campos de Araújo, Luiz Otávio Campos da Silva, Eduardo Quirino Arguelho de Queiroz, Urbano Gomes Pinto de Abreu, Rodrigo da Costa Gomes, Hemerson Pistori
    Computers and Electronics in Agriculture, 2020
  • Recognition of Pantaneira cattle breed using computer vision and convolutional neural networks
    Fabricio de Lima Weber, Vanessa Aparecida de Moraes Weber, Geazy Vilharva Menezes, Adair da Silva Oliveira Junior, Daniela Arestides Alves, Marcus Vinicius Morais de Oliveira, Edson Takashi Matsubara, Hemerson Pistori, Urbano Gomes Pinto de Abreu
    Computers and Electronics in Agriculture, 2020
  • Prediction of Girolando cattle weight by means of body measurements extracted from images
    Vanessa Aparecida de Moraes Weber, Fabricio de Lima Weber, Rodrigo da Costa Gomes, Adair da Silva Oliveira, Geazy Vilharva Menezes, Urbano Gomes Pinto de Abreu, Nícolas Alessandro de Souza Belete, Hemerson Pistori
    Revista Brasileira De Zootecnia, 2020
    The objective with this study was to analyze the body measurements of Girolando cattle, as well as measurements extracted from their images, to generate a model to understand which measures further explain the cattle body weight. Therefore, the experiment physically measured 34 Girolando cattle (two males and 32 females), for the following traits: heart girth (HGP), circumference of the abdomen, body length, occipito-ischial length, wither height, and hip height. In addition, images of the dorsum and the body lateral [...]
  • Use of computational vision and UAVs in livestock: A Literature review
    Fabricio de Lima Weber, Maria Istela Cagnin, Débora Maria Barroso Paiva, Vanessa Aparecida de Moraes Weber, Sérgio Raposo de Medeiros, Rodrigo da Costa Gomes, Hemerson Pistori
    Iberian Conference on Information Systems and Technologies Cisti, 2019
    New technologies have been developed with the objective of supporting the activity of livestock. Within these technologies, the computational vision stands out by defining techniques and developing tools in order to allow automatic analysis of images, such as those captured by UAVs (Unmanned Aerial Vehicles). These can be used for different purposes in livestock precision such as identification and counting of the animals. This paper presents the results of a literature review about the use of UAVs and computational vision to support livestock activities with the objective of identifying, cataloging and classifying the existing works in this context.
  • Software for automatic evaluation of stretch marks
    Victor Borges Jussiani, Hemerson Pistori, Alessandro dos Santos Ferreira, Gercina Gonçalves da Silva, Fabíola Picosse, Ediléia Bagatin, Fabricio de Lima Weber, Vanessa Aparecida de Moraes Weber
    Iberian Conference on Information Systems and Technologies Cisti, 2019
    Considering that the current protocols in the evaluation of stretch marks are based on the visual clinical examination of the striated skin and in the measure of the same, this article aims to assist the professionals of the dermatology through data for decision making in the diagnosis and follow-up of the treatment of the striations . In order to do so, a software supported by computational vision and machine learning techniques was developed, aiming to collect images and analyze them to identify striae. From a database of images annotated by specialists in dermatology, color and texture attributes of the segments were extracted, which were later classified by the Random Forest algorithm, which presented a 99.92% correct classification of the striae. In addition, metrics were analyzed that indicated that although the streak superpixels were correctly classified, other classes were classified incorrectly.

RECENT SCHOLAR PUBLICATIONS

  • Bovine facial recognition through muzzles
    VA Andrade Porto, K. R., de Andrade Porto, J. V., de Lima Weber, F ...
    Academia AI and Applications 2 (1) , 2026
    2026
  • A new Siamese network loss for cattle facial recognition in a Few-Shot learning scenario
    J Porto, G Higa, V Weber, F Weber, N Loebens, P Claure, L de Almeida, ...
    AgriEngineering 6 (3), 2941-2954 , 2024
    2024
    Citations: 4
  • Exploring cluster analysis in Nelore cattle visual score attribution
    A de Oliveira Bezerra, VA de Moraes Weber, F de Lima Weber, ...
    Smart Agricultural Technology 8, 100489 , 2024
    2024
    Citations: 3
  • Andrological classification of bulls evaluated by machine learning.
    SA Isler, UGP de ABREU, E NOGUEIRA, VAM WEBER, FO PEDRO, ...
    2024
  • Classificação andrológica de touros avaliada por machine learning.
    SA ISLER, UGP de ABREU, E NOGUEIRA, VAM WEBER, FO PEDRO, ...
    2024
  • Supervised computer vision system for weight group classification of fingerlings
    A da SO Junior, AKV da Silva, MCB Pache, DA Sant’Ana, AM Carneiro, ...
    Workshop de Visão Computacional (WVC), 142-147 , 2023
    2023
  • Counting cattle in UAV images using convolutional neural network
    F de Lima Weber, VA de Moraes Weber, PH de Moraes, ET Matsubara, ...
    Remote Sensing Applications: Society and Environment 29, 100900 , 2023
    2023
    Citations: 40
  • Fingerlings mass estimation: A comparison between deep and shallow learning algorithms
    ASO Junior, DA Sant’Ana, MCB Pache, V Garcia, VA de Moares Weber, ...
    Smart Agricultural Technology 1, 100020 , 2021
    2021
    Citations: 13
  • An Investigation of Parameter Optimization in Fingerling Counting Problems
    ASO Junior, MCB Pache, FPC Rezende, DA Sant’Ana, ...
    Workshop de Visão Computacional (WVC), 7-12 , 2021
    2021
  • Cattle weight estimation using active contour models and regression trees Bagging
    VAM Weber, F de Lima Weber, A da Silva Oliveira, G Astolfi, GV Menezes, ...
    Computers and electronics in agriculture 179, 105804 , 2020
    2020
    Citations: 87
  • Recognition of Pantaneira cattle breed using computer vision and convolutional neural networks
    F de Lima Weber, VA de Moraes Weber, GV Menezes, ASO Junior, ...
    Computers and Electronics in Agriculture 175, 105548 , 2020
    2020
    Citations: 72
  • A. d. SO Junior, DA Alves, MVM de Oliveira, ET Matsubara, H. Pistori, and UGP de Abreu,“Recognition of pantaneira cattle breed using computer vision and convolutional neural …
    F de Lima Weber, VA de Moraes Weber, GV Menezes
    Computers and Electronics in Agriculture 175, 105548 , 2020
    2020
    Citations: 5
  • Prediction of Girolando cattle weight by means of body measurements extracted from images
    VAM Weber, FL Weber, RC Gomes, AS Oliveira Junior, GV Menezes, ...
    Revista Brasileira de Zootecnia 49, e20190110 , 2020
    2020
    Citations: 82
  • Determination of number of termite mounds supported by computational vision
    VA de Moraes Weber, F de Lima Weber, E Silveira, GL de Oliveira, ...
    Workshop de Visão Computacional (WVC), 85-90 , 2019
    2019
    Citations: 1
  • 2D4D Reader
    FL WEBER, VAM Weber, H PISTORI, AS OLIVEIRA JUNIOR, ...
    BR Patent BR5120190010-4 , 2019
    2019
  • Reconhecimento de bovino pantaneiro utilizando visão computacional através da rede neural convolucional: resultados preliminares.
    FL WEBER, VAM WEBER, G MENEZES, AS OLIVEIRA JUNIOR, ...
    2019
    Citations: 1
  • Sistematizando Práticas para Administrar
    CRM da Silva
    2019
  • Utilização de visão computacional e VANTs na pecuária: uma revisão da literatura Use of computational vision and UAVs in livestock
    F de Lima Weber, MI Cagnin, DMB Paiva, U Facom, G do Sul, ...
    14th Iberian Conference on Information Systems and Technologies (CISTI … , 2019
    2019
    Citations: 6
  • Software para Avaliação Automática de Estrias Software for Automatic Evaluation of Stretch Marks
    VB Jussiani, H Pistori, U Agropecuária, A Ferreira dos Santos, ...
    2019
  • Identificação de bovinos das raças Nelore e Girolando usando redes neurais profundas
    F de Lima Weber, V Aparecida de Moraes Weber, H Pistori, ...
    Anais do Encontro Científico da Zootecnia UEMS 1 (1) , 2018
    2018

MOST CITED SCHOLAR PUBLICATIONS

  • Cattle weight estimation using active contour models and regression trees Bagging
    VAM Weber, F de Lima Weber, A da Silva Oliveira, G Astolfi, GV Menezes, ...
    Computers and electronics in agriculture 179, 105804 , 2020
    2020
    Citations: 87
  • Prediction of Girolando cattle weight by means of body measurements extracted from images
    VAM Weber, FL Weber, RC Gomes, AS Oliveira Junior, GV Menezes, ...
    Revista Brasileira de Zootecnia 49, e20190110 , 2020
    2020
    Citations: 82
  • Recognition of Pantaneira cattle breed using computer vision and convolutional neural networks
    F de Lima Weber, VA de Moraes Weber, GV Menezes, ASO Junior, ...
    Computers and Electronics in Agriculture 175, 105548 , 2020
    2020
    Citations: 72
  • Counting cattle in UAV images using convolutional neural network
    F de Lima Weber, VA de Moraes Weber, PH de Moraes, ET Matsubara, ...
    Remote Sensing Applications: Society and Environment 29, 100900 , 2023
    2023
    Citations: 40
  • Fingerlings mass estimation: A comparison between deep and shallow learning algorithms
    ASO Junior, DA Sant’Ana, MCB Pache, V Garcia, VA de Moares Weber, ...
    Smart Agricultural Technology 1, 100020 , 2021
    2021
    Citations: 13
  • Utilização de visão computacional e VANTs na pecuária: uma revisão da literatura Use of computational vision and UAVs in livestock
    F de Lima Weber, MI Cagnin, DMB Paiva, U Facom, G do Sul, ...
    14th Iberian Conference on Information Systems and Technologies (CISTI … , 2019
    2019
    Citations: 6
  • A. d. SO Junior, DA Alves, MVM de Oliveira, ET Matsubara, H. Pistori, and UGP de Abreu,“Recognition of pantaneira cattle breed using computer vision and convolutional neural …
    F de Lima Weber, VA de Moraes Weber, GV Menezes
    Computers and Electronics in Agriculture 175, 105548 , 2020
    2020
    Citations: 5
  • A new Siamese network loss for cattle facial recognition in a Few-Shot learning scenario
    J Porto, G Higa, V Weber, F Weber, N Loebens, P Claure, L de Almeida, ...
    AgriEngineering 6 (3), 2941-2954 , 2024
    2024
    Citations: 4
  • Exploring cluster analysis in Nelore cattle visual score attribution
    A de Oliveira Bezerra, VA de Moraes Weber, F de Lima Weber, ...
    Smart Agricultural Technology 8, 100489 , 2024
    2024
    Citations: 3
  • Determination of number of termite mounds supported by computational vision
    VA de Moraes Weber, F de Lima Weber, E Silveira, GL de Oliveira, ...
    Workshop de Visão Computacional (WVC), 85-90 , 2019
    2019
    Citations: 1
  • Reconhecimento de bovino pantaneiro utilizando visão computacional através da rede neural convolucional: resultados preliminares.
    FL WEBER, VAM WEBER, G MENEZES, AS OLIVEIRA JUNIOR, ...
    2019
    Citations: 1
  • Bovine facial recognition through muzzles
    VA Andrade Porto, K. R., de Andrade Porto, J. V., de Lima Weber, F ...
    Academia AI and Applications 2 (1) , 2026
    2026
  • Andrological classification of bulls evaluated by machine learning.
    SA Isler, UGP de ABREU, E NOGUEIRA, VAM WEBER, FO PEDRO, ...
    2024
  • Classificação andrológica de touros avaliada por machine learning.
    SA ISLER, UGP de ABREU, E NOGUEIRA, VAM WEBER, FO PEDRO, ...
    2024
  • Supervised computer vision system for weight group classification of fingerlings
    A da SO Junior, AKV da Silva, MCB Pache, DA Sant’Ana, AM Carneiro, ...
    Workshop de Visão Computacional (WVC), 142-147 , 2023
    2023
  • An Investigation of Parameter Optimization in Fingerling Counting Problems
    ASO Junior, MCB Pache, FPC Rezende, DA Sant’Ana, ...
    Workshop de Visão Computacional (WVC), 7-12 , 2021
    2021
  • 2D4D Reader
    FL WEBER, VAM Weber, H PISTORI, AS OLIVEIRA JUNIOR, ...
    BR Patent BR5120190010-4 , 2019
    2019
  • Sistematizando Práticas para Administrar
    CRM da Silva
    2019
  • Software para Avaliação Automática de Estrias Software for Automatic Evaluation of Stretch Marks
    VB Jussiani, H Pistori, U Agropecuária, A Ferreira dos Santos, ...
    2019
  • Identificação de bovinos das raças Nelore e Girolando usando redes neurais profundas
    F de Lima Weber, V Aparecida de Moraes Weber, H Pistori, ...
    Anais do Encontro Científico da Zootecnia UEMS 1 (1) , 2018
    2018