activity
20162024
most citedBioLeaf: a professional mobile application to measure foliar damage caused by insect herbivory

127 citations · 129 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Using Deep Learning for Morphological Classification in Pigs with a Focus on Sanitary Monitoring

Eduardo Bedin, Junior Silva Souza, Gabriel Toshio Hirokawa Higa +4

The aim of this paper is to evaluate the use of D-CNN (Deep Convolutional Neural Networks) algorithms to classify pig body conditions in normal or not normal conditions, with a foc…

cs.CV2024

Pig aggression classification using CNN, Transformers and Recurrent Networks

Junior Silva Souza, Eduardo Bedin, Gabriel Toshio Hirokawa Higa +2

The development of techniques that can be used to analyze and detect animal behavior is a crucial activity for the livestock sector, as it is possible to monitor the stress and ani…

eess.IV2024

Aedes aegypti Egg Counting with Neural Networks for Object Detection

Micheli Nayara de Oliveira Vicente, Gabriel Toshio Hirokawa Higa, João Vitor de Andrade Porto +6

Aedes aegypti is still one of the main concerns when it comes to disease vectors. Among the many ways to deal with it, there are important protocols that make use of egg numbers in…

eess.IV20241 cited

Exploring Cluster Analysis in Nelore Cattle Visual Score Attribution

Alexandre de Oliveira Bezerra, Rodrigo Goncalves Mateus, Vanessa Ap. de Moraes Weber +5

Assessing the biotype of cattle through human visual inspection is a very common and important practice in precision cattle breeding. This paper presents the results of a correlati…

eess.IV2024

A New Machine Learning Dataset of Bulldog Nostril Images for Stenosis Degree Classification

Gabriel Toshio Hirokawa Higa, Joyce Katiuccia Medeiros Ramos Carvalho, Paolo Brito Pascoalini Zanoni +2

Brachycephaly, a conformation trait in some dog breeds, causes BOAS, a respiratory disorder that affects the health and welfare of the dogs with various symptoms. In this paper, a…

cs.CV20231 cited

MTLSegFormer: Multi-task Learning with Transformers for Semantic Segmentation in Precision Agriculture

Diogo Nunes Goncalves, Jose Marcato Junior, Pedro Zamboni +4

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 indepe…