462 citations · 595 across the 10 of their papers we have counts for
11 papers
Livestock Fish Larvae Counting using DETR and YOLO based Deep Networks
Daniel Ortega de Carvalho, Luiz Felipe Teodoro Monteiro, Fernanda Marques Bazilio +2
Counting fish larvae is an important, yet demanding and time consuming, task in aquaculture. In order to address this problem, in this work, we evaluate four neural network archite…
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…
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…
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…
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…
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…
Smartphone region-wise image indoor localization using deep learning for indoor tourist attraction
Gabriel Toshio Hirokawa Higa, Rodrigo Stuqui Monzani, Jorge Fernando da Silva Cecatto +4
Smart indoor tourist attractions, such as smart museums and aquariums, usually require a significant investment in indoor localization devices. The smartphone Global Positional Sys…
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…
A Deep Learning Approach Based on Graphs to Detect Plantation Lines
Diogo Nunes Gonçalves, Mauro dos Santos de Arruda, Hemerson Pistori +8
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…
A Review on Deep Learning in UAV Remote Sensing
Lucas Prado Osco, José Marcato Junior, Ana Paula Marques Ramos +7
Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language,…
BioLeaf: a professional mobile application to measure foliar damage caused by insect herbivory
Bruno Machado, Jonatan Orue, Mauro Arruda +7
Soybean is one of the ten greatest crops in the world, answering for billion-dollar businesses every year. This crop suffers from insect herbivory that costs millions from producer…