Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Interest
Topics
Details

Details

001
Publications

2020

Evaluation of Machine Learning Algorithms for Automated Management of Wireless Links

Authors
Frias, F; Marcal, ARS; Prior, R; Moreira, W; Oliveira Jr, A;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
Machine learning, a subfield of artificial intelligence, has been widely used to automate tasks usually performed by humans. Some applications of these techniques are understanding network traffic behavior, predicting it, classifying it, fixing its faults, identifying malware applications, and preventing deliberate attacks. The goal of this work is to use machine learning algorithms to classify, in separate procedures, the errors of the network, their causes, and possible fixes. Our application case considers the WiBACK wireless system, from which we also obtained the data logs used to produce this paper. WiBACK is a collection of software and hardware with auto-configuration and self-management capabilities, designed to reduce CAPEX and OPEX costs. A principal components analysis is performed, followed by the application of decision trees, k nearest neighbors, and support vector machines. A comparison between the results obtained by the algorithms trained with the original data sets, balanced data sets, and the principal components data is performed. We achieve weighted F1-score between 0.93 and 0.99 with the balanced data, 0.88 and 0.96 with the original unbalanced data, and 0.81 and 0.89 with the Principal Components Analysis. © 2020, Springer Nature Switzerland AG.

2020

Measuring Surface and Volume of a Spheroid-Shaped 3D Object from a Single Image

Authors
Marcal, ARS; Santos, EMDS;

Publication
SN Computer Science

Abstract

2019

Development of an image-based system to assess agricultural fertilizer spreader pattern

Authors
Marcal, ARS; Cunha, M;

Publication
COMPUTERS AND ELECTRONICS IN AGRICULTURE

Abstract
An Automatic Calibration of Fertilizers (ACFert) system was developed, for use with centrifugal, pendulum or other types of broadcast spreaders which distribute dry granular agricultural materials on the top of the soil. The ACfert is based on image processing techniques and includes a specially designed mat, which should be placed in the ground for spreaders calibration. A set of images acquired outdoor by a standard device (simple camera) is used to extract information about the spreader distribution pattern. Each image is processed independently, providing as output two numerical values for each grid element present in the image - the number of fertilizers/seeds counted, and its numerical label. The performance of ACFert was evaluated for automatic granules detection using a set of manual counting measurements of nitrate fertilizer and wheat seeds. A total of 185 images acquired with two mobiles devices were used with a total of 498 quadrilateral elements observed and analysed. The overall mean absolute relative error between counting and computed by the ACFert system, were 0.75 +/- 0.75% for fertilizer and 2.12 +/- 1.68% for wheat. This near real-time calibration tool is a very low cost system that can be easily used on field, providing results to support accurate spreader calibration in near real time for different types of fertilizers or seeds.

2019

Automatic classification of coral images using colour and textures

Authors
Caridade, CMR; Marcal, ARS;

Publication
CEUR Workshop Proceedings

Abstract
The purpose of this work is to address the imageCLEF 2019 coral challenge - to develop a system for the detection and identification of substrates in coral images. Initially a revision of the 13 classes was carried out by identifying a number of sub-classes for some substrates. Four features were considered - 3 related to greyscale intensity (1) and texture (2), and 1 related to the colour content. The Breiman's Random forest algorithm was used to classify the corals in one of 13 classes defined. A classification accuracy of about 49% was obtained.

2019

Image Based Estimation of Fruit Phytopathogenic Lesions Area

Authors
Marcal, ARS; Santos, EMDS; Tavares, F;

Publication
Pattern Recognition and Image Analysis - Lecture Notes in Computer Science

Abstract

Supervised
thesis

2020

Análise e projeção comportamental de clientes na área de venda de cimento e derivados

Author
Catarina Teixeira Pinto

Institution
UP-FCUP

2020

Automated monitoring of WiBACK traffic behavior: application of machine learning algorithms to a wireless system

Author
Francisca Guimarães Frias Rodrigues

Institution
UP-FCUP

2019

Visão Computacional para veículos aéreos não tripulados (UAV)

Author
Mónica Cristina Gandra da Rocha Salgado

Institution
UP-FCUP

2018

Extração Automática de Texto em Imagem/Vídeo

Author
Pedro Cunha Travassos

Institution
UP-FCUP

2018

Towards automatic identification of woods from microscopic images

Author
Aurora Losa Ramalho Martins

Institution
UP-FCUP