Manuel J. Fonseca

Corrigendum: Towards an automated approach for understanding problematic gaming

Ana Paula Afonso, Manuel J. Fonseca, Joana Cardoso, Beltrán Vázquez

\textbf{Introduction}:Video games have become increasingly popular worldwide, attracting billions of gamers across diverse demographics. While studies have highlighted their potential benefits, concerns about problematic gaming behaviors have also emerged. Conditions such as Internet Gaming Disorder (IGD) have been recognized by major health …

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Towards an automated approach for understanding problematic gaming

Ana Paula Afonso, Manuel J. Fonseca, Joana Cardoso, Beltrán Vázquez

Introduction: Video games have become increasingly popular worldwide, attracting billions of gamers across diverse demographics. While studies have highlighted their potential benefits, concerns about problematic gaming behaviors have also emerged. Conditions such as Internet Gaming Disorder (IGD) have been recognized by major …

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Cleenex: Support for User Involvement during an Iterative Data Cleaning Process

João L. M. Pereira, Manuel J. Fonseca, Antónia Lopes, Héléna Galhardas

The existence of large amounts of data increases the probability of occurring data quality problems. A data cleaning process that corrects these problems is usually an iterative process, because it may need to be re-executed and refined to produce high-quality data. Moreover, …

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Polygon Detection from a Set of Lines

Alfredo Ferreira, Manuel J. Fonseca, Joaquim Armando Jorge

Detecting polygons defined by a set of line segments in a plane is an important step in analyzing vector drawings. This paper presents an approach combining several algorithms to detect basic polygons from arbitrary line segments. The resulting algorithm runs in polynomial …

Annotate Smarter, not Harder: Using Active Learning to Reduce Emotional Annotation Effort

Soraia M. Alarcão, Vânia Mendonça, Carolina Maruta, Manuel J. Fonseca

The success of supervised models for emotion recognition on images heavily depends on the availability of images properly annotated. Although millions of images are presently available, only a few are annotated with reliable emotional information. Current emotion recognition solutions either use large …

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metaFERA: a meta-framework for creating emotion recognition frameworks for physiological signals

João Oliveira, Soraia M. Alarcão, Teresa Chambel, Manuel J. Fonseca

Abstract Recognizing emotions from physiological signals has proven to be important in various scenarios. To assist in developing emotion recognizers, software frameworks and toolboxes have emerged, offering ready-to-use components. However,these have limitations regarding the type of physiological signals supported, the recognition steps …

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That's AWESOME: Awareness While Experiencing and Surfing On Movies through Emotions

Teresa Chambel, Patrí­cia Arriaga, Manuel J. Fonseca, Thibault Langlois et autres

This paper presents the AWESOME research project: Awareness While Experiencing and Surfing On Movies through Emotions, which focused on the role of emotions in movies, aiming to enhance viewers' emotional awareness while searching, accessing and watching movies. The project addressed challenges such …

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ExpertosLF: dynamic late fusion of CBIR systems using online learning with relevance feedback

Soraia M. Alarcão, Vânia Mendonça, Carolina Maruta, Manuel J. Fonseca

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VENOUS GANGRENE: REMINDING A VASCULAR CATASTROPHE

Joana Cruz Silva, Anabela Gonçalves, Manuel J. Fonseca

A 85 year-old, female patient, with an active colon neoplasm, was diagnosed with extensive ilio-femoro-popliteal deep vein thrombosis. She presented with severe oedema of the left lower limb and a cyanotic foot. Pedal pulses were palpable. Despite immediate anticoagulation, the patient expired …

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Unfolding Handcrafted Features Contribution in Cnns for Valence and Arousal Estimation in Images

Soraia M. Alarcão, Cláudia Ribeiro, Nuno M. García, Carolina Maruta et autres

Predicting Exact Valence and Arousal Values from EEG

Filipe Galvão, Soraia M. Alarcão, Manuel J. Fonseca

Recognition of emotions from physiological signals, and in particular from electroencephalography (EEG), is a field within affective computing gaining increasing relevance. Although researchers have used these signals to recognize emotions, most of them only identify a limited set of emotional states (e.g., …

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Polygon Detection from a Set of Lines

Manuel J. Fonseca, Joaquim Armando Jorge

Detecting polygons defined by a set of line segments in a plane is an important step in the analysis of vectorial drawings. This paper presents an approach that combines several algorithms to detect basic polygons from a set of arbitrary line segments. …

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