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Author F.Negin; Pau Rodriguez; M.Koperski; A.Kerboua; Jordi Gonzalez; J.Bourgeois; E.Chapoulie; P.Robert; F.Bremond
Title PRAXIS: Towards automatic cognitive assessment using gesture recognition Type Journal Article
Year 2018 Publication (up) Expert Systems with Applications Abbreviated Journal ESWA
Volume 106 Issue Pages 21-35
Keywords
Abstract Praxis test is a gesture-based diagnostic test which has been accepted as diagnostically indicative of cortical pathologies such as Alzheimer’s disease. Despite being simple, this test is oftentimes skipped by the clinicians. In this paper, we propose a novel framework to investigate the potential of static and dynamic upper-body gestures based on the Praxis test and their potential in a medical framework to automatize the test procedures for computer-assisted cognitive assessment of older adults.

In order to carry out gesture recognition as well as correctness assessment of the performances we have recollected a novel challenging RGB-D gesture video dataset recorded by Kinect v2, which contains 29 specific gestures suggested by clinicians and recorded from both experts and patients performing the gesture set. Moreover, we propose a framework to learn the dynamics of upper-body gestures, considering the videos as sequences of short-term clips of gestures. Our approach first uses body part detection to extract image patches surrounding the hands and then, by means of a fine-tuned convolutional neural network (CNN) model, it learns deep hand features which are then linked to a long short-term memory to capture the temporal dependencies between video frames.
We report the results of four developed methods using different modalities. The experiments show effectiveness of our deep learning based approach in gesture recognition and performance assessment tasks. Satisfaction of clinicians from the assessment reports indicates the impact of framework corresponding to the diagnosis.
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Notes ISE Approved no
Call Number Admin @ si @ NRK2018 Serial 3669
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Author Debora Gil; Oriol Ramos Terrades; Raquel Perez
Title Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution Type Book Chapter
Year 2021 Publication (up) Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15 Abbreviated Journal
Volume 15 Issue Pages 89–93
Keywords
Abstract Abnormalities in radiomic measures correlate to genomic alterations prone to alter the outcome of personalized anti-cancer treatments. TOPiomics is a new method for the early detection of variations in tumor imaging phenotype from a topological structure in multi-view radiomic spaces.
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Publisher Springer Nature Place of Publication Editor
Language Summary Language Original Title
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Area Expedition Conference
Notes IAM; DAG; 600.120; 600.145; 600.139 Approved no
Call Number Admin @ si @ GRP2021 Serial 3594
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Author Katerine Diaz; Francesc J. Ferri
Title Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes Type Book Whole
Year 2013 Publication (up) Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Los métodos basados en subespacios son una herramienta muy utilizada en aplicaciones de visión por computador. Aquí se presentan y validan algunos algoritmos que hemos propuesto en este campo de investigación. El primer algoritmo está relacionado con una extensión del método de vectores comunes discriminantes con kernel, que reinterpreta el espacio nulo de la matriz de dispersión intra-clase del conjunto de entrenamiento para obtener las características discriminantes. Dentro de los métodos basados en subespacios existen diferentes tipos de entrenamiento. Uno de los más populares, pero no por ello uno de los más eficientes, es el aprendizaje por lotes. En este tipo de aprendizaje, todas las muestras del conjunto de entrenamiento tienen que estar disponibles desde el inicio. De este modo, cuando nuevas muestras se ponen a disposición del algoritmo, el sistema tiene que ser reentrenado de nuevo desde cero. Una alternativa a este tipo de entrenamiento es el aprendizaje incremental. Aquí­ se proponen diferentes algoritmos incrementales del método de vectores comunes discriminantes.
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Series Editor Series Title Abbreviated Series Title
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ISSN ISBN 978-3-639-55339-0 Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ DiF2013 Serial 2440
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Author M. Bressan; Jordi Vitria
Title Improving Naive Bayes using Class Conditional ICA Type Miscellaneous
Year 2002 Publication (up) F. Garijo, J. Riquelme, M. Toro, (Eds.), Advances in Artificial Intelligece–Iberamia, LNAI 2527: 1–10, Springer Verlag Series. Abbreviated Journal
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ BrV2002d Serial 278
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Author David Masip; Agata Lapedriza; Jordi Vitria
Title Measuring External Face Appearance for Face Classification. Type Book Chapter
Year 2007 Publication (up) Face Recognition, Ed. Kresimir Delac and Mislav Grgic, pp. 287–307, ISBN 978–3–902613–03–5, I–Tech Education and Publishing Abbreviated Journal
Volume Issue Pages
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Abstract
Address Vienna (Austria)
Corporate Author Thesis
Publisher Place of Publication Editor
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ MLV2007b Serial 940
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Author Ciprian Corneanu; Meysam Madadi; Sergio Escalera; Aleix Martinez
Title Explainable Early Stopping for Action Unit Recognition Type Conference Article
Year 2020 Publication (up) Faces and Gestures in E-health and welfare workshop Abbreviated Journal
Volume Issue Pages 693-699
Keywords
Abstract A common technique to avoid overfitting when training deep neural networks (DNN) is to monitor the performance in a dedicated validation data partition and to stop
training as soon as it saturates. This only focuses on what the model does, while completely ignoring what happens inside it.
In this work, we open the “black-box” of DNN in order to perform early stopping. We propose to use a novel theoretical framework that analyses meso-scale patterns in the topology of the functional graph of a network while it trains. Based on it,
we decide when it transitions from learning towards overfitting in a more explainable way. We exemplify the benefits of this approach on a state-of-the art custom DNN that jointly learns local representations and label structure employing an ensemble of dedicated subnetworks. We show that it is practically equivalent in performance to early stopping with patience, the standard early stopping algorithm in the literature. This proves beneficial for AU recognition performance and provides new insights into how learning of AUs occurs in DNNs.
Address Virtual; November 2020
Corporate Author Thesis
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Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference FGW
Notes HUPBA; Approved no
Call Number Admin @ si @ CME2020 Serial 3514
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Author Anna Esposito; Terry Amorese; Nelson Maldonato; Alessandro Vinciarelli; Maria Ines Torres; Sergio Escalera; Gennaro Cordasco
Title Seniors’ ability to decode differently aged facial emotional expressions Type Conference Article
Year 2020 Publication (up) Faces and Gestures in E-health and welfare workshop Abbreviated Journal
Volume Issue Pages 716-722
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Abstract
Address Virtual; November 2020
Corporate Author Thesis
Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference FGW
Notes HUPBA Approved no
Call Number Admin @ si @ EAM2020 Serial 3515
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Author Anna Esposito; Italia Cirillo; Antonietta Esposito; Leopoldina Fortunati; Gian Luca Foresti; Sergio Escalera; Nikolaos Bourbakis
Title Impairments in decoding facial and vocal emotional expressions in high functioning autistic adults and adolescents Type Conference Article
Year 2020 Publication (up) Faces and Gestures in E-health and welfare workshop Abbreviated Journal
Volume Issue Pages 667-674
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Abstract
Address Virtual; November 2020
Corporate Author Thesis
Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference FGW
Notes HUPBA Approved no
Call Number Admin @ si @ ECE2020 Serial 3516
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Author Fadi Dornaika; Bogdan Raducanu
Title Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation Type Book Chapter
Year 2012 Publication (up) Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions Abbreviated Journal
Volume Issue Pages 157-178
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Address
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Publisher NOVA Publishers Place of Publication Editor S.E. Carter
Language Summary Language Original Title
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Notes OR;MV Approved no
Call Number Admin @ si @ DoR2012 Serial 2183
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Author E. Pastor; A. Agueda; Juan Andrade; M. Muñoz; Y. Perez; E. Planas
Title Computing the rate of spread of linear flame fronts by thermal image processing Type Journal
Year 2006 Publication (up) Fire Safety Journal, 41(8):569–579 Abbreviated Journal
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Notes Approved no
Call Number Admin @ si @ PAA2006 Serial 679
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Author Pau Baiget; Eric Sommerlade; I. Reid; Jordi Gonzalez
Title Finding Prototypes to Estimate Trajectory Development in Outdoor Scenarios Type Conference Article
Year 2008 Publication (up) First International Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences BMVC 2008, Abbreviated Journal
Volume Issue Pages 27–34
Keywords
Abstract
Address Leed
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-935251-9-4 Medium
Area Expedition Conference THEMIS’
Notes ISE Approved no
Call Number ISE @ ise @ BSR2008 Serial 1008
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Author Ognjen Rudovic; Xavier Roca
Title Building Temporale Templates for Human Behaviour Classification Type Conference Article
Year 2008 Publication (up) First International Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences BMVC 2008, Abbreviated Journal
Volume Issue Pages 79–88
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Abstract
Address Leeds (UK)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-935251-9-4 Medium
Area Expedition Conference THEMIS’
Notes ISE Approved no
Call Number ISE @ ise @ RuR2008 Serial 1009
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Author Carles Fernandez; Pau Baiget; Jordi Gonzalez
Title Cognitive-Guided Semantic Exploitation in Video Surveillance Interfaces Type Conference Article
Year 2008 Publication (up) First International Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences. BMVC 2008, Abbreviated Journal
Volume Issue Pages 53–60
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Abstract
Address Leeds (UK)
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Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-935251-9-4 Medium
Area Expedition Conference THEMIS’
Notes ISE Approved no
Call Number ISE @ ise @ FBG2008 Serial 1010
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Author Jordi Gonzalez; Thomas B. Moeslund
Title Tracking Humans for the Evaluation of their Motion in Image Sequences Type Book Whole
Year 2008 Publication (up) First International Workshop, THEMIS Abbreviated Journal
Volume Issue Pages
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Address Leeds (UK)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-935251-9-4 Medium
Area Expedition Conference THEMIS
Notes Approved no
Call Number ISE @ ise @ GMW2008 Serial 1002
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Author Mohammad Momeny; Ali Asghar Neshat; Ahmad Jahanbakhshi; Majid Mahmoudi; Yiannis Ampatzidis; Petia Radeva
Title Grading and fraud detection of saffron via learning-to-augment incorporated Inception-v4 CNN Type Journal Article
Year 2023 Publication (up) Food Control Abbreviated Journal FC
Volume 147 Issue Pages 109554
Keywords
Abstract Saffron is a well-known product in the food industry. It is one of the spices that are sometimes adulterated with the sole motive of gaining more economic profit. Today, machine vision systems are widely used in controlling the quality of food and agricultural products as a new, non-destructive, and inexpensive approach. In this study, a machine vision system based on deep learning was used to detect fraud and saffron quality. A dataset of 1869 images was created and categorized in 6 classes including: dried saffron stigma using a dryer; dried saffron stigma using pressing method; pure stem of saffron; sunflower; saffron stem mixed with food coloring; and corn silk mixed with food coloring. A Learning-to-Augment incorporated Inception-v4 Convolutional Neural Network (LAII-v4 CNN) was developed for grading and fraud detection of saffron in images captured by smartphones. The best policies of data augmentation were selected with the proposed LAII-v4 CNN using images corrupted by Gaussian, speckle, and impulse noise to address overfitting the model. The proposed LAII-v4 CNN compared with regular CNN-based methods and traditional classifiers. Ensemble of Bagged Decision Trees, Ensemble of Boosted Decision Trees, k-Nearest Neighbor, Random Under-sampling Boosted Trees, and Support Vector Machine were used for classification of the features extracted by Histograms of Oriented Gradients and Local Binary Patterns, and selected by the Principal Component Analysis. The results showed that the proposed LAII-v4 CNN with an accuracy of 99.5% has achieved the best performance by employing batch normalization, Dropout, and leaky ReLU.
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Notes MILAB Approved no
Call Number Admin @ si @ MNJ2023 Serial 3882
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