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Author (up) Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; M. Gomez; Antonio Tovar; L. Cano; C. Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva
Title Ecografia Intracoronaria: Segmentacio Automatica de area de la llum Type Journal
Year 2002 Publication Revista Societat Catalana de Cardiologia Abbreviated Journal
Volume 4 Issue 4 Pages 42
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Abstract
Address Barcelona
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ISSN ISBN Medium
Area Expedition Conference XIVe Congres de la Societat Catalana de Cardiologia
Notes MILAB;IAM Approved no
Call Number BCNPCL @ bcnpcl @ RMF2002 Serial 435
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Author (up) Patricia Suarez; Henry Velesaca; Dario Carpio; Angel Sappa
Title Corn kernel classification from few training samples Type Journal
Year 2023 Publication Artificial Intelligence in Agriculture Abbreviated Journal
Volume 9 Issue Pages 89-99
Keywords
Abstract This article presents an efficient approach to classify a set of corn kernels in contact, which may contain good, or defective kernels along with impurities. The proposed approach consists of two stages, the first one is a next-generation segmentation network, trained by using a set of synthesized images that is applied to divide the given image into a set of individual instances. An ad-hoc lightweight CNN architecture is then proposed to classify each instance into one of three categories (ie good, defective, and impurities). The segmentation network is trained using a strategy that avoids the time-consuming and human-error-prone task of manual data annotation. Regarding the classification stage, the proposed ad-hoc network is designed with only a few sets of layers to result in a lightweight architecture capable of being used in integrated solutions. Experimental results and comparisons with previous approaches showing both the improvement in accuracy and the reduction in time are provided. Finally, the segmentation and classification approach proposed can be easily adapted for use with other cereal types.
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Area Expedition Conference
Notes MSIAU Approved no
Call Number Admin @ si @ SVC2023 Serial 3892
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Author (up) Patrick Brandao; O. Zisimopoulos; E. Mazomenos; G. Ciutib; Jorge Bernal; M. Visentini-Scarzanell; A. Menciassi; P. Dario; A. Koulaouzidis; A. Arezzo; D.J. Hawkes; D. Stoyanov
Title Towards a computed-aided diagnosis system in colonoscopy: Automatic polyp segmentation using convolution neural networks Type Journal
Year 2018 Publication Journal of Medical Robotics Research Abbreviated Journal JMRR
Volume 3 Issue 2 Pages
Keywords convolutional neural networks; colonoscopy; computer aided diagnosis
Abstract Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC) and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), ne-tune them and study their capabilities for polyp segmentation and detection. We additionally use Shape-from-Shading (SfS) to recover depth and provide a richer representation of the tissue's structure in colonoscopy images. Depth is
incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation IU of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp
detection, the top performing models we propose surpass the current state of the art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the rst work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance.
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Notes MV; no menciona Approved no
Call Number BZM2018 Serial 2976
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Author (up) Pau Rodriguez; Jordi Gonzalez; Josep M. Gonfaus; Xavier Roca
Title Integrating Vision and Language in Social Networks for Identifying Visual Patterns of Personality Traits Type Journal
Year 2019 Publication International Journal of Social Science and Humanity Abbreviated Journal IJSSH
Volume 9 Issue 1 Pages 6-12
Keywords
Abstract Social media, as a major platform for communication and information exchange, is a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topics. In this sense, user text interactions are widely used to sense the whys of certain social user’s demands and cultural- driven interests. However, the knowledge embedded in the 1.8 billion pictures which are uploaded daily in public profiles has just started to be exploited. Following this trend on visual-based social analysis, we present a novel methodology based on neural networks to build a combined image-and-text based personality trait model, trained with images posted together with words found highly correlated to specific personality traits. So, the key contribution in this work is to explore whether OCEAN personality trait modeling can be addressed based on images, here called MindPics, appearing with certain tags with psychological insights. We found that there is a correlation between posted images and the personality estimated from their accompanying texts. Thus, the experimental results are consistent with previous cyber-psychology results based on texts, suggesting that images could also be used for personality estimation: classification results on some personality traits show that specific and characteristic visual patterns emerge, in essence representing abstract concepts. These results open new avenues of research for further refining the proposed personality model under the supervision of psychology experts, and to further substitute current textual personality questionnaires by image-based ones.
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Area Expedition Conference
Notes ISE; 600.119 Approved no
Call Number Admin @ si @ RGG2019 Serial 3414
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Author (up) Petia Radeva; Jordi Vitria
Title Corkinspect: Statistical Learning of Natural Material Type Journal
Year 2004 Publication Italian Beverage Technology, 13(38):11–18 Abbreviated Journal
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Address
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Notes OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ RaV2004b Serial 514
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Author (up) R. Clariso; David Masip; A. Rius
Title Student projects empowering mobile learning in higher education Type Journal
Year 2014 Publication Revista de Universidad y Sociedad del Conocimiento Abbreviated Journal RUSC
Volume 11 Issue Pages 192-207
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Address
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1698-580X ISBN Medium
Area Expedition Conference
Notes OR;MV Approved no
Call Number Admin @ si @ CMR2014 Serial 2619
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Author (up) Razieh Rastgoo; Kourosh Kiani; Sergio Escalera
Title Real-time Isolated Hand Sign Language RecognitioN Using Deep Networks and SVD Type Journal
Year 2022 Publication Journal of Ambient Intelligence and Humanized Computing Abbreviated Journal
Volume 13 Issue Pages 591–611
Keywords
Abstract One of the challenges in computer vision models, especially sign language, is real-time recognition. In this work, we present a simple yet low-complex and efficient model, comprising single shot detector, 2D convolutional neural network, singular value decomposition (SVD), and long short term memory, to real-time isolated hand sign language recognition (IHSLR) from RGB video. We employ the SVD method as an efficient, compact, and discriminative feature extractor from the estimated 3D hand keypoints coordinators. Despite the previous works that employ the estimated 3D hand keypoints coordinates as raw features, we propose a novel and revolutionary way to apply the SVD to the estimated 3D hand keypoints coordinates to get more discriminative features. SVD method is also applied to the geometric relations between the consecutive segments of each finger in each hand and also the angles between these sections. We perform a detailed analysis of recognition time and accuracy. One of our contributions is that this is the first time that the SVD method is applied to the hand pose parameters. Results on four datasets, RKS-PERSIANSIGN (99.5±0.04), First-Person (91±0.06), ASVID (93±0.05), and isoGD (86.1±0.04), confirm the efficiency of our method in both accuracy (mean+std) and time recognition. Furthermore, our model outperforms or gets competitive results with the state-of-the-art alternatives in IHSLR and hand action recognition.
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Notes HUPBA; no proj Approved no
Call Number Admin @ si @ RKE2022a Serial 3660
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Author (up) Robert Benavente; Maria Vanrell; Ramon Baldrich
Title Parametric Fuzzy Sets for Automatic Color Naming Type Journal
Year 2008 Publication Journal of the Optical Society of America A Abbreviated Journal
Volume 25 Issue 10 Pages 2582–2593
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Address
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Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ BVB2008 Serial 1004
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Author (up) Robert Benavente; Maria Vanrell; Ramon Baldrich
Title A data set for fuzzy colour naming Type Journal
Year 2006 Publication Color Research & Application, 31(1):48–56 Abbreviated Journal
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Address
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Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ BVB2006 Serial 590
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Author (up) Robert Benavente; Maria Vanrell; Ramon Baldrich
Title Estimation of Fuzzy Sets for Computational Colour Categorization Type Journal
Year 2004 Publication Color Research and Application, 29(5):342–353 (IF: 0.739) Abbreviated Journal
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Address
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ BVB2004 Serial 484
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Author (up) Roger Max Calle Quispe; Maya Aghaei Gavari; Eduardo Aguilar Torres
Title Towards real-time accurate safety helmets detection through a deep learning-based method Type Journal
Year 2023 Publication Ingeniare. Revista chilena de ingenieria Abbreviated Journal
Volume 31 Issue 12 Pages
Keywords
Abstract 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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Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @ CAA2023 Serial 3846
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Author (up) S. Chanda; Umapada Pal; Oriol Ramos Terrades
Title Word-Wise Thai and Roman Script Identification Type Journal
Year 2009 Publication ACM Transactions on Asian Language Information Processing Abbreviated Journal TALIP
Volume 8 Issue 3 Pages 1-21
Keywords
Abstract In some Thai documents, a single text line of a printed document page may contain words of both Thai and Roman scripts. For the Optical Character Recognition (OCR) of such a document page it is better to identify, at first, Thai and Roman script portions and then to use individual OCR systems of the respective scripts on these identified portions. In this article, an SVM-based method is proposed for identification of word-wise printed Roman and Thai scripts from a single line of a document page. Here, at first, the document is segmented into lines and then lines are segmented into character groups (words). In the proposed scheme, we identify the script of a character group combining different character features obtained from structural shape, profile behavior, component overlapping information, topological properties, and water reservoir concept, etc. Based on the experiment on 10,000 data (words) we obtained 99.62% script identification accuracy from the proposed scheme.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1530-0226 ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ CPR2009f Serial 1869
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Author (up) S. Tanimoto; N. Bruining; David Rotger; Petia Radeva; J. Ligthart; R.T. van Domburg; P. W. Serryus
Title Late Stent Recoil of the Bioabsorbable Everolimus Eluting Coronary Stent and its Relationship with Stent Struts Distribution and Plaque Morphology Type Journal
Year 2008 Publication Journal of the American College of Cardiology, vol. 52(20):1616–1620 Abbreviated Journal
Volume Issue Pages
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Abstract
Address Bridgewater, NJ 08807(USA)
Corporate Author Thesis
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Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ TBR2008 Serial 953
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Author (up) Sergio Escalera
Title Multi-Modal Human Behaviour Analysis from Visual Data Sources Type Journal
Year 2013 Publication ERCIM News journal Abbreviated Journal ERCIM
Volume 95 Issue Pages 21-22
Keywords
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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Language Summary Language Original Title
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Series Volume Series Issue Edition
ISSN 0926-4981 ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ Esc2013 Serial 2361
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Author (up) Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin
Title Subclass Problem-Dependent Design for Error-Correcting Output Codes Type Journal
Year 2008 Publication IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.30(6):1041–1054 Abbreviated Journal
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Address
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Area Expedition Conference
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ ETP2008 Serial 951
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