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Author |
O. Fors; A. Richichi; Xavier Otazu; J. Nuñez |
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Title |
A new wavelet-based approach for the automated treatment of large sets of lunar occultation data |
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2008 |
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Astronomy and Astrohysics |
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480 |
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297–304 |
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CAT @ cat @ FRO2008 |
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934 |
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Ester Fornells; Manuel De Armas; Maria Teresa Anguera; Sergio Escalera; Marcos Antonio Catalán; Josep Moya |
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Title |
Desarrollo del proyecto del Consell Comarcal del Baix Llobregat “Buen Trato a las personas mayores y aquellas en situación de fragilidad con sufrimiento emocional: Hacia un envejecimiento saludable” |
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2018 |
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Informaciones Psiquiatricas |
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232 |
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47-59 |
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0210-7279 |
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HUPBA; no menciona |
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Admin @ si @ FAA2018 |
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3214 |
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Author |
Josep Llados; J. Lopez-Krahe; D. Archambault |
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Title |
Special Issue on Information Technologies for Visually Impaired People |
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2007 |
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Novatica |
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186 |
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4-7 |
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DAG @ dag @ LLA2007a |
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903 |
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Carolina Malagelada; Fosca De Iorio; Fernando Azpiroz; Anna Accarino; Santiago Segui; Petia Radeva; Juan R. Malagelada |
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Title |
New Insight Into Intestinal Motor Function via Noninvasive Endoluminal Image Analysis |
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2008 |
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Gastroenterology |
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135 |
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4 |
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1155–1162 |
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MILAB |
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BCNPCL @ bcnpcl @ MDA2008 |
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1040 |
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Author |
Yasuko Sugito; Trevor Canham; Javier Vazquez; Marcelo Bertalmio |
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Title |
A Study of Objective Quality Metrics for HLG-Based HDR/WCG Image Coding |
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Journal |
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Year |
2021 |
Publication |
SMPTE Motion Imaging Journal |
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SMPTE |
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130 |
Issue |
4 |
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53 - 65 |
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Abstract |
In this work, we study the suitability of high dynamic range, wide color gamut (HDR/WCG) objective quality metrics to assess the perceived deterioration of compressed images encoded using the hybrid log-gamma (HLG) method, which is the standard for HDR television. Several image quality metrics have been developed to deal specifically with HDR content, although in previous work we showed that the best results (i.e., better matches to the opinion of human expert observers) are obtained by an HDR metric that consists simply in applying a given standard dynamic range metric, called visual information fidelity (VIF), directly to HLG-encoded images. However, all these HDR metrics ignore the chroma components for their calculations, that is, they consider only the luminance channel. For this reason, in the current work, we conduct subjective evaluation experiments in a professional setting using compressed HDR/WCG images encoded with HLG and analyze the ability of the best HDR metric to detect perceivable distortions in the chroma components, as well as the suitability of popular color metrics (including ΔITPR , which supports parameters for HLG) to correlate with the opinion scores. Our first contribution is to show that there is a need to consider the chroma components in HDR metrics, as there are color distortions that subjects perceive but that the best HDR metric fails to detect. Our second contribution is the surprising result that VIF, which utilizes only the luminance channel, correlates much better with the subjective evaluation scores than the metrics investigated that do consider the color components. |
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no |
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SCV2021 |
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3671 |
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Author |
Sergio Escalera |
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Title |
Multi-Modal Human Behaviour Analysis from Visual Data Sources |
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Journal |
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Year |
2013 |
Publication |
ERCIM News journal |
Abbreviated Journal |
ERCIM |
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Volume |
95 |
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Pages |
21-22 |
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Abstract |
The Human Pose Recovery and Behaviour Analysis group (HuPBA), University of Barcelona, is developing a line of research on multi-modal analysis of humans in visual data. The novel technology is being applied in several scenarios with high social impact, including sign language recognition, assisted technology and supported diagnosis for the elderly and people with mental/physical disabilities, fitness conditioning, and Human Computer Interaction. |
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0926-4981 |
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HuPBA;MILAB |
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no |
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Call Number |
Admin @ si @ Esc2013 |
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2361 |
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Author |
Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; Antonio Tovar; Vicente del Valle; Aura Hernandez-Sabate; Debora Gil; Petia Radeva |
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Title |
Utilizacion de la estructura de los campos vectoriales para la deteccion de la Adventicia en imagenes de Ecografia Intracoronaria |
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Journal |
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Year |
2004 |
Publication |
Revista Española de Cardiología |
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REC |
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Volume |
57 |
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2 |
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100 |
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MILAB;IAM |
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no |
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BCNPCL @ bcnpcl @ RMF2004 |
Serial |
566 |
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Author |
Xavier Otazu; Maria Vanrell; C. Alejandro Parraga |
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Title |
Multiresolution Wavelet Framework Models Brightness Induction Effects |
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Journal |
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Year |
2008 |
Publication |
Vision Research |
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VR |
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Volume |
48 |
Issue |
5 |
Pages |
733–751 |
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CIC |
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no |
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Call Number |
CAT @ cat @ OVP2008a |
Serial |
927 |
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Author |
Zeynep Yucel; Albert Ali Salah; Çetin Meriçli; Tekin Meriçli; Roberto Valenti; Theo Gevers |
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Title |
Joint Attention by Gaze Interpolation and Saliency |
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Year |
2013 |
Publication |
IEEE Transactions on cybernetics |
Abbreviated Journal |
T-CIBER |
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Volume |
43 |
Issue |
3 |
Pages |
829-842 |
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Abstract |
Joint attention, which is the ability of coordination of a common point of reference with the communicating party, emerges as a key factor in various interaction scenarios. This paper presents an image-based method for establishing joint attention between an experimenter and a robot. The precise analysis of the experimenter's eye region requires stability and high-resolution image acquisition, which is not always available. We investigate regression-based interpolation of the gaze direction from the head pose of the experimenter, which is easier to track. Gaussian process regression and neural networks are contrasted to interpolate the gaze direction. Then, we combine gaze interpolation with image-based saliency to improve the target point estimates and test three different saliency schemes. We demonstrate the proposed method on a human-robot interaction scenario. Cross-subject evaluations, as well as experiments under adverse conditions (such as dimmed or artificial illumination or motion blur), show that our method generalizes well and achieves rapid gaze estimation for establishing joint attention. |
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2168-2267 |
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ALTRES;ISE |
Approved |
no |
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Call Number |
Admin @ si @ YSM2013 |
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2363 |
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Author |
Oriol Pujol; Sergio Escalera; Petia Radeva |
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Title |
An Incremental Node Embedding Technique for Error Correcting Output Codes |
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2008 |
Publication |
Pattern Recognition |
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PR |
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41 |
Issue |
2 |
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713–725 |
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MILAB;HuPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ PER2008 |
Serial |
942 |
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Author |
Jordi Esquirol; Cristina Palmero; Vanessa Bayo; Miquel Angel Cos; Sergio Escalera; David Sanchez; Maider Sanchez; Noelia Serrano; Mireia Relats |
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Title |
Automatic RBG-depth-pressure anthropometric analysis and individualised sleep solution prescription |
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2017 |
Publication |
Journal of Medical Engineering & Technology |
Abbreviated Journal |
JMET |
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Volume |
41 |
Issue |
6 |
Pages |
486-497 |
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Abstract |
INTRODUCTION:
Sleep surfaces must adapt to individual somatotypic features to maintain a comfortable, convenient and healthy sleep, preventing diseases and injuries. Individually determining the most adequate rest surface can often be a complex and subjective question.
OBJECTIVES:
To design and validate an automatic multimodal somatotype determination model to automatically recommend an individually designed mattress-topper-pillow combination.
METHODS:
Design and validation of an automated prescription model for an individualised sleep system is performed through a single-image 2 D-3 D analysis and body pressure distribution, to objectively determine optimal individual sleep surfaces combining five different mattress densities, three different toppers and three cervical pillows.
RESULTS:
A final study (n = 151) and re-analysis (n = 117) defined and validated the model, showing high correlations between calculated and real data (>85% in height and body circumferences, 89.9% in weight, 80.4% in body mass index and more than 70% in morphotype categorisation).
CONCLUSIONS:
Somatotype determination model can accurately prescribe an individualised sleep solution. This can be useful for healthy people and for health centres that need to adapt sleep surfaces to people with special needs. Next steps will increase model's accuracy and analise, if this prescribed individualised sleep solution can improve sleep quantity and quality; additionally, future studies will adapt the model to mattresses with technological improvements, tailor-made production and will define interfaces for people with special needs. |
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HUPBA; no menciona |
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no |
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Admin @ si @ EPB2017 |
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3010 |
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Author |
Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol |
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Title |
La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals |
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2016 |
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Lligall, Revista Catalana d'Arxivística |
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39 |
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20-46 |
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DAG; 600.097 |
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Admin @ si @ FLR2016 |
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2897 |
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Author |
J. Pladellorens; Joan Serrat; A. Castell; M.J. Yzuel |
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Title |
Using mathematical morphology to determine left ventricular contours. |
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1993 |
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Physics in Medicine and Biology. |
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38 |
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12 |
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1877––1894 |
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ADAS @ adas @ PSC1993 |
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146 |
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Hugo Berti; Angel Sappa; Osvaldo Agamennoni |
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Improved Dynamic Window Approach by Using Lyapunov Stability Criteria |
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2008 |
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Latin American Applied Research |
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38 |
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4 |
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289–298 |
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ADAS |
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ADAS @ adas @ BSA2008 |
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1056 |
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Author |
Roger Max Calle Quispe; Maya Aghaei Gavari; Eduardo Aguilar Torres |
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Title |
Towards real-time accurate safety helmets detection through a deep learning-based method |
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2023 |
Publication |
Ingeniare. Revista chilena de ingenieria |
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31 |
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12 |
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Occupational safety is a fundamental activity in industries and revolves around the management of the necessary controls that must be present to mitigate occupational risks. These controls include verifying the use of Personal Protection Equipment (PPE). Within PPE, safety helmets are vital to reducing severe or fatal consequences caused by head injuries. This problem has been addressed recently by various research based on deep learning to detect the usage of safety helmets by the present people in the industrial field.
These works have achieved promising results for safety helmet detection using object detection methods from the YOLO family. In this work, we propose to analyze the performance of Scaled-YOLOv4, a novel model of the YOLO family that has yet to be previously studied for this problem. The performance of the Scaled-YOLOv4 is evaluated on two public databases, carefully selected among the previously proposed datasets for the occupational safety framework. We demonstrate the superiority of Scaled-YOLOv4 in terms of mAP and Fl-score concerning the previous works for both databases. Further, we summarize the currently available datasets for safety helmet detection purposes and discuss their suitability. |
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MILAB |
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no |
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Admin @ si @ CAA2023 |
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3846 |
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