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About

About

Luis F. Teixeira holds a Ph.D. in Electrical and Computer Engineering from Universidade do Porto in the area of computer vision (2009). Currently he is an Assistant Professor at the Department of Informatics Engineering, Faculdade de Engenharia da Universidade do Porto, and a researcher at INESC TEC. Previously he was a researcher at INESC Porto (2001-2008), Visiting Researcher at the University of Victoria (2006), and Senior Scientist at Fraunhofer AICOS (2008-2013). His current research interest include: computer vision, machine learning and interactive systems.

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Topics
Details

Details

001
Publications

2022

From Captions to Explanations: A Multimodal Transformer-based Architecture for Natural Language Explanation Generation

Authors
Torto, IR; Cardoso, JS; Teixeira, LF;

Publication
Pattern Recognition and Image Analysis - 10th Iberian Conference, IbPRIA 2022, Aveiro, Portugal, May 4-6, 2022, Proceedings

Abstract

2022

Hybrid Quality Inspection for the Automotive Industry: Replacing the Paper-Based Conformity List through Semi-Supervised Object Detection and Simulated Data

Authors
Rio-Torto, I; Campanico, AT; Pinho, P; Filipe, V; Teixeira, LF;

Publication
APPLIED SCIENCES-BASEL

Abstract
The still prevalent use of paper conformity lists in the automotive industry has a serious negative impact on the performance of quality control inspectors. We propose instead a hybrid quality inspection system, where we combine automated detection with human feedback, to increase worker performance by reducing mental and physical fatigue, and the adaptability and responsiveness of the assembly line to change. The system integrates the hierarchical automatic detection of the non-conforming vehicle parts and information visualization on a wearable device to present the results to the factory worker and obtain human confirmation. Besides designing a novel 3D vehicle generator to create a digital representation of the non conformity list and to collect automatically annotated training data, we apply and aggregate in a novel way state-of-the-art domain adaptation and pseudo labeling methods to our real application scenario, in order to bridge the gap between the labeled data generated by the vehicle generator and the real unlabeled data collected on the factory floor. This methodology allows us to obtain, without any manual annotation of the real dataset, an example-based F1 score of 0.565 in an unconstrained scenario and 0.601 in a fixed camera setup (improvements of 11 and 14.6 percentage points, respectively, over a baseline trained with purely simulated data). Feedback obtained from factory workers highlighted the usefulness of the proposed solution, and showed that a truly hybrid assembly line, where machine and human work in symbiosis, increases both efficiency and accuracy in automotive quality control.

2022

Detection of Epilepsy in EEGs Using Deep Sequence Models - A Comparative Study

Authors
Marques, M; Silva Lourenço, Cd; Teixeira, LF;

Publication
Pattern Recognition and Image Analysis - 10th Iberian Conference, IbPRIA 2022, Aveiro, Portugal, May 4-6, 2022, Proceedings

Abstract

2022

Pattern Recognition and Image Analysis - 10th Iberian Conference, IbPRIA 2022, Aveiro, Portugal, May 4-6, 2022, Proceedings

Authors
Pinho, AJ; Georgieva, P; Teixeira, LF; Sánchez, JA;

Publication
IbPRIA

Abstract

2022

A survey on attention mechanisms for medical applications: are we moving towards better algorithms?

Authors
Goncalves, T; Rio Torto, I; Teixeira, LF; Cardoso, JS;

Publication
IEEE Access

Abstract

Supervised
thesis

2021

Graph-SLAM Approach for Indoor UAV Localization in Warehouse Logistics Applications

Author
JOSÉ FILIPE DA SILVA OLIVEIRA ANTUNES

Institution
IPP-ISEP

2021

Predicting TV Audiences Based on Physiological Data and Twitter Activity: a machine-learning approach

Author
Sara Manuela Cortinhas Pereira

Institution
UP-FEP

2021

Combining machine learning and deep learning approaches to detect cervical cancer in cytology images

Author
Eduardo Luís Pinheiro da Silva

Institution
UP-FEUP

2021

Detection of Epilepsy in EEGs using sequence models

Author
Miguel Filipe Saraiva Marques

Institution
UP-FEUP

2021

Section Detection in an Automatic Pipeline for Mapping Brain Activation in the Mouse

Author
Pedro Gonçalves Neto

Institution
UP-FEUP