Littérature scientifique sur le sujet « Soft Biometry »
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Articles de revues sur le sujet "Soft Biometry"
Różyło-Kalinowska, Ingrid, Jakub Kuryło, Stanisław Nowak, Magdalena Piskórz, Katarzyna Portka et Magdalena Kozek. « Ultrasonographic biometry of soft tissues in patients with gingival recessions. Preliminary report ». Journal of Stomatology 72, no 3 (2019) : 106–11. http://dx.doi.org/10.5114/jos.2019.87523.
Texte intégralMadadi, Meysam, Sergio Escalera, Jordi Gonzàlez, F. Xavier Roca et Felipe Lumbreras. « Multi-part body segmentation based on depth maps for soft biometry analysis ». Pattern Recognition Letters 56 (avril 2015) : 14–21. http://dx.doi.org/10.1016/j.patrec.2015.01.012.
Texte intégralHebbar, Shripad, Sukriti Malaviya et Sunanda Bharatnur. « INTEGRATION OF FETAL MID THIGH SOFT TISSUE THICKNESS IN ULTRASOUND BIRTH WEIGHT ESTIMATION FORMULA INCREASES THE ACCURACY OF FETAL WEIGHT ESTIMATION NEAR TERM ». Asian Journal of Pharmaceutical and Clinical Research 11, no 4 (1 avril 2018) : 446. http://dx.doi.org/10.22159/ajpcr.2018.v11i4.23776.
Texte intégralCinar, Hatice Burcu, et Mekin Sezik. « Correlation of Fractional Limb Volume Measurements with Neonatal Morphometric Indices ». Gynecologic and Obstetric Investigation 86, no 1-2 (2021) : 94–99. http://dx.doi.org/10.1159/000512749.
Texte intégralLewis, Jennifer R., Andrea E. Knellinger, Ashraf M. Mahmoud et Thomas F. Mauger. « Effect of Soft Contact Lenses on Optical Measurements of Axial Length and Keratometry for Biometry in Eyes with Corneal Irregularities ». Investigative Opthalmology & ; Visual Science 49, no 8 (1 août 2008) : 3371. http://dx.doi.org/10.1167/iovs.07-1247.
Texte intégralGarcia Flores, Jose, Ritu Mogra, Monica Sadowski et Jon Hyett. « Prediction of Birth Weight and Neonatal Adiposity Using Ultrasound Assessment of Soft Tissue Parameters in Addition to Two-Dimensional Conventional Biometry ». Fetal Diagnosis and Therapy 48, no 3 (2021) : 201–8. http://dx.doi.org/10.1159/000510637.
Texte intégralTarutta, E. P., S. V. Milash et M. V. Epishina. « Accommodation Dynamics in Children Wearing Bifocal Soft Contact Lenses with High Addition Power ». EYE GLAZ 23, no 1 (23 mars 2021) : 7–14. http://dx.doi.org/10.33791/2222-4408-2021-1-7-14.
Texte intégralTamano, Luana Tieko Omena, Beethoven Brandão Correia de Lima, Joseane Da Silva et Daniel de Magalhães Araujo. « FISHING, PROCESSING, COMMERCIALIZATION AND A PROPOSE TO FISHERY WASTE REUSE OF SURURU Mytella falcata IN THE MUNDAÚ LAGOON, MACEIÓ – AL, BRAZIL ». Caminhos de Geografia 21, no 76 (3 août 2020) : 306–20. http://dx.doi.org/10.14393/rcg217652255.
Texte intégralKharel, Milan, et Damodar Thapa Chhetry. « Description on some rescued turtles and their translocation at Turtle Rescue and Conservation Centre (TRCC), Sanischare, Jhapa ». BIBECHANA 11 (10 mai 2014) : 141–48. http://dx.doi.org/10.3126/bibechana.v11i0.10394.
Texte intégralChuprov, A. D., V. L. Kim et A. E. Voronina. « Evaluation of the efficiency of refractive error correction using phakic intraocular lens implantation ». Acta Biomedica Scientifica 7, no 2 (24 mai 2022) : 167–73. http://dx.doi.org/10.29413/abs.2022-7.2.17.
Texte intégralThèses sur le sujet "Soft Biometry"
Guo, Bingchen. « Soft biometric fusion for subject recognition at a distance ». Thesis, University of Southampton, 2018. https://eprints.soton.ac.uk/423611/.
Texte intégralTerhörst, Philipp [Verfasser], Arjan [Akademischer Betreuer] Kuijper, Dieter [Akademischer Betreuer] Fellner et Vitomir [Akademischer Betreuer] Struc. « Mitigating Soft-Biometric Driven Bias and Privacy Concerns in Face Recognition Systems / Philipp Terhörst ; Arjan Kuijper, Dieter Fellner, Vitomir Struc ». Darmstadt : Universitäts- und Landesbibliothek, 2021. http://d-nb.info/1233785060/34.
Texte intégralSoriano, Tolosa Antonio. « Fusión de datos estadísticamente dependientes en sistemas de detección ». Doctoral thesis, Universitat Politècnica de València, 2014. http://hdl.handle.net/10251/34780.
Texte intégralSoriano Tolosa, A. (2013). Fusión de datos estadísticamente dependientes en sistemas de detección [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34780
TESIS
CAPLOVA, ZUZANA. « MORPHOLOGY OF THE FACE AS A POSTMORTEM PERSONAL IDENTIFIER ». Doctoral thesis, Università degli Studi di Milano, 2018. http://hdl.handle.net/2434/544095.
Texte intégralSegalin, Cristina. « A Social Signal Processing Perspective on Computational Aesthetics : Theories and Applications ». Doctoral thesis, 2016. http://hdl.handle.net/11562/941657.
Texte intégralEveryday, we are exposed to various images and videos thanks to the social media, like Facebook, Youtube, Flickr, Instagram and others.In this scenario, the use of expressing preferences for a given multimedia content (for example by the use of liking mechanisms) has become pervasive and massive, becoming a social mass phenomenon.One of the main findings of cognitive sciences is that automatic processes of which we are unaware shape, to a significant extent, our perception of the environment. The phenomenon applies not only to the real world, but also to multimedia data we consume every day. Whenever we look at pictures, watch a video or listen to audio recordings, our conscious attention efforts focus on the observable content, but our cognition spontaneously perceives intentions, beliefs, values, attitudes and other constructs that, while being outside of our conscious awareness, still shape our reactions and behavior. So far, multimedia technologies have neglected such a phenomenon to a large extent. This thesis argues that taking into account cognitive effects is possible and it can also improve multimedia approaches. For this purpose we take into account Computational Aesthetics and Social Signal Processing principles under a computational point of view. On one side Computational Aesthetics makes applicable aesthetic decision in a similar fashion as human can allowing to multimedia technologies to learn, model and evaluate a common sense of beauty. On the other side,Social Signal Processing field has the aim of modeling with algorithms cognitive processes that codify social signal and that lead us to interact with a particular way with people or to prefer a particular image or video. This represents an invaluable opportunity for CA because human aesthetic response is formed by a combination of genetic predisposition, cultural assimilation, and unique individual experience and indeed it can be learned from online pictures using the wisdom of crowds.The thesis focuses on images as a first attempt in this direction.The motivation of why focusing on pictures are many: from one side, taking pictures is the action most commonly performed with mobile phones, on the other side, users either post online original images or videos or share and redistribute those posted by others. To this aim the thesis presents a study on personal aesthetics, where the goal is to recognize people and their characteristics by considering the images they like by developing several hybrid approaches using generative models and regressors.The general idea assumes that, given a set of preferred images, it is possible to extract a set of features individuating discriminative visual patterns, that can be used to infer personal characteristics of the subject that preferred them.As first contribution we propose a soft biometric system, that allows to discriminate an individual from another using the images he/she likes. The study and development of biometric system have become of paramount importance for both identification of individual and security applications and recommendation systems. On a dataset of 200 users and 40K images, the developed frameworks gives 97\% of probability of guessing the correct user using 5 preferred images as biometric template; as for the verification capability, the equal error rate is 0.11.Furthermore, we developed a system able to infer the personality of a subject using the images preferred by him/her. The motivation is that whenever we meet a person for the first time, but also when we observe her in video recordings, or we interact with an artifact displaying human-like behavior or with the multimedia material she shares online, we tend to attribute personality traits to her. The process is spontaneous and unconscious. While not necessarily accurate, the process still influences significantly our behavior towards others, especially when in comes to social interactions. As a supporting proof-of-concept, the thesis shows that there are visual patterns correlated with the personality traits of Flickr users to a statistically significant extent, and that the personality traits (both self-assessed and attributed by others) of those users can be inferred from the images these latter mark as ``favorite''. One of the most important part of the thesis has been the collection of the PsychoFlickr corpus, composed of 60K images of 300 Flickr users annotated in terms of personality traits both self and attributed by 22 assessors. The prediction are performed using multiple approaches (multiple instance regression approach and a deep learning framework), reaching a correlation up to 0.68 and an accuracy up to 0.69 between actual and predicted traits.The prediction of traits attributed from others achieve higher results compared to the self-assessed ones: the reason is that pictures dominate the personality impressions that the judges develop and the consensus across the judges is statistically significant. These two conditions help the regression approaches to achieve higher performances. When the users self-assess their personality, they take into account information that is not available in the favorite pictures like, e.g., personal history, inner state, education,etc.. Therefore, this does not allow the regression approaches to achieve high performances. This is an important finding as it can help to better understand the social behavior of people, to design artificial agents capable of eliciting the perception of predefined desirable traits and providing suggestions on how to manage online impressions using favorite pictures.
Middendorff, Christopher. « Multi-biometric approaches to ear biometrics and soft biometrics ». 2009. http://etd.nd.edu/ETD-db/theses/available/etd-11062009-203812/.
Texte intégralThesis directed by Kevin W. Bowyer for the Department of Computer Science and Engineering. "November 2009." Includes bibliographical references (leaves 153-157).
Terhörst, Philipp. « Mitigating Soft-Biometric Driven Bias and Privacy Concerns in Face Recognition Systems ». Phd thesis, 2021. https://tuprints.ulb.tu-darmstadt.de/18515/7/Dissertation_Terhoerst_final.pdf.
Texte intégralYaghoubi, Ehsan. « Soft Biometric Analysis : MultiPerson and RealTime Pedestrian Attribute Recognition in Crowded Urban Environments ». Doctoral thesis, 2021. http://hdl.handle.net/10400.6/12081.
Texte intégralThis thesis was prepared at the University of Beria Interior, IT Instituto de Telecomunicações, Soft Computing and Image Analysis Laboratory (SOCIA Lab), Covilhã Delegation, and was submitted to the University of Beira Interior for defense in a public examination session.
Livres sur le sujet "Soft Biometry"
David, Hutchison. Computational Intelligence Methods for Bioinformatics and Biostatistics : 5th International Meeting, CIBB 2008 Vietri sul Mare, Italy, October 3-4, 2008 Revised Selected Papers. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
Trouver le texte intégralDeng, Hepu. Artificial Intelligence and Computational Intelligence : International Conference, AICI 2009, Shanghai, China, November 7-8, 2009. Proceedings. Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2009.
Trouver le texte intégralSoft Computing For Recognition Based On Biometrics. Springer, 2010.
Trouver le texte intégralChowdhary, Chiranji Lal. Intelligent Systems : Advances in Biometric Systems, Soft Computing, Image Processing, and Data Analytics. Apple Academic Press, Incorporated, 2019.
Trouver le texte intégralChowdhary, Chiranji Lal. Intelligent Systems : Advances in Biometric Systems, Soft Computing, Image Processing, and Data Analytics. Apple Academic Press, Incorporated, 2019.
Trouver le texte intégralIntelligent Systems : Advances in Biometric Systems, Soft Computing, Image Processing, and Data Analytics. Taylor & Francis Group, 2019.
Trouver le texte intégralChowdhary, Chiranji Lal. Intelligent Systems : Advances in Biometric Systems, Soft Computing, Image Processing, and Data Analytics. Apple Academic Press, Incorporated, 2019.
Trouver le texte intégralDeng, Hepu, Jingsheng Lei et Duoqian Miao. Artificial Intelligence and Computational Intelligence : Second International Conference, AICI 2011, Taiyuan, China, September 24-25, 2011, Proceedings, Part II. Springer, 2011.
Trouver le texte intégralChapitres de livres sur le sujet "Soft Biometry"
Siwik, Leszek, Lukasz Mozgowoj et Krzysztof Rzecki. « From Biometry to Signature-As-A-Service : The Idea, Architecture and Realization ». Dans Artificial Intelligence and Soft Computing, 200–209. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39384-1_18.
Texte intégralSamangooei, Sina, et Mark S. Nixon. « On Semantic Soft-Biometric Labels ». Dans Biometric Authentication, 3–15. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13386-7_1.
Texte intégralJaha, Emad Sami, et Mark S. Nixon. « Analysing Soft Clothing Biometrics for Retrieval ». Dans Biometric Authentication, 234–45. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13386-7_19.
Texte intégralJain, Anil K., Sarat C. Dass et Karthik Nandakumar. « Soft Biometric Traits for Personal Recognition Systems ». Dans Biometric Authentication, 731–38. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_99.
Texte intégralXiao, Shudi, Shuiwang Li et Qijun Zhao. « Low-Quality 3D Face Recognition with Soft Thresholding ». Dans Biometric Recognition, 419–27. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86608-2_46.
Texte intégralGomolka, Zbigniew, et Tomasz Lewandowski. « The Biometric Signals Processing ». Dans Advances in Soft Computing, 637–44. Berlin, Heidelberg : Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75175-5_80.
Texte intégralFranke, Katrin, et Javier Ruiz-del-Solar. « Soft-Biometrics : Soft-Computing Technologies for Biometric-Applications ». Dans Advances in Soft Computing — AFSS 2002, 171–77. Berlin, Heidelberg : Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45631-7_24.
Texte intégralRot, Peter, Peter Peer et Vitomir Štruc. « Detecting Soft-Biometric Privacy Enhancement ». Dans Handbook of Digital Face Manipulation and Detection, 391–411. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87664-7_18.
Texte intégralYe, Huixing, Roland Hu, Huimin Yu et Robert Ian Damper. « Face Recognition Based on Adaptive Soft Histogram Local Binary Patterns ». Dans Biometric Recognition, 62–70. Cham : Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02961-0_8.
Texte intégralJain, Anil K., Karthik Nandakumar, Xiaoguang Lu et Unsang Park. « Integrating Faces, Fingerprints, and Soft Biometric Traits for User Recognition ». Dans Biometric Authentication, 259–69. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25976-3_24.
Texte intégralActes de conférences sur le sujet "Soft Biometry"
D'Angelo, Angela, et Jean-Luc Dugelay. « Color based soft biometry for hooligans detection ». Dans 2010 IEEE International Symposium on Circuits and Systems - ISCAS 2010. IEEE, 2010. http://dx.doi.org/10.1109/iscas.2010.5537508.
Texte intégralWang, Yuan-Fang, Edward Y. Chang et Ken P. Cheng. « A video analysis framework for soft biometry security surveillance ». Dans the third ACM international workshop. New York, New York, USA : ACM Press, 2005. http://dx.doi.org/10.1145/1099396.1099412.
Texte intégralGarg, Rishabh, Anisha Arora, Saurabh Singh et Shipra Saraswat. « Biometric Authentication using Soft Biometric Traits ». Dans 2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2018. http://dx.doi.org/10.1109/pdgc.2018.8745766.
Texte intégralFuentes-Hernandez, Canek, Youngrak Park, Kyungjin Kim, Wen-Fang Chou, Felipe A. Larrain, Samuel Graham, Olivier N. Pierron et Bernard Kippelen. « Flexible and stretchable low-noise organic photodiodes for biometric monitoring ». Dans Latin America Optics and Photonics Conference. Washington, D.C. : Optica Publishing Group, 2022. http://dx.doi.org/10.1364/laop.2022.m4b.6.
Texte intégralKashyap, Abhay L., Sergey Tulyakov et Venu Govindaraju. « Facial behavior as a soft biometric ». Dans 2012 5th IAPR International Conference on Biometrics (ICB). IEEE, 2012. http://dx.doi.org/10.1109/icb.2012.6199772.
Texte intégralChhaya, Niyati, et Tim Oates. « Joint inference of soft biometric features ». Dans 2012 5th IAPR International Conference on Biometrics (ICB). IEEE, 2012. http://dx.doi.org/10.1109/icb.2012.6199794.
Texte intégralMoi, Sim Hiew, Nazeema Binti Abdul Rahim, Puteh Saad, Pang Li Sim, Zalmiyah Zakaria et Subariah Ibrahim. « Iris Biometric Cryptography for Identity Document ». Dans 2009 International Conference of Soft Computing and Pattern Recognition. IEEE, 2009. http://dx.doi.org/10.1109/socpar.2009.149.
Texte intégralZhou, Zhi, Glen Hong Ting Ong et Earn Khwang Teoh. « Soft-biometric detection based on supervised learning ». Dans 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV). IEEE, 2014. http://dx.doi.org/10.1109/icarcv.2014.7064310.
Texte intégralLyle, Jamie R., Philip E. Miller, Shrinivas J. Pundlik et Damon L. Woodard. « Soft biometric classification using periocular region features ». Dans 2010 IEEE Fourth International Conference On Biometrics : Theory, Applications And Systems (BTAS). IEEE, 2010. http://dx.doi.org/10.1109/btas.2010.5634537.
Texte intégralJain, Anil K., Sarat C. Dass et Karthik Nandakumar. « Can soft biometric traits assist user recognition ? » Dans Defense and Security, sous la direction de Anil K. Jain et Nalini K. Ratha. SPIE, 2004. http://dx.doi.org/10.1117/12.542890.
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