Academic literature on the topic 'Verification de visage'
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Journal articles on the topic "Verification de visage":
Kumar, Mr Mukesh. "YOLO-FaceNet Fusion: Innovative System for Facial Recognition and Feature Extraction." International Scientific Journal of Engineering and Management 03, no. 05 (May 25, 2024): 1–9. http://dx.doi.org/10.55041/isjem01802.
Wang, Yi Min, Hong Bo Zhang, Chun Hui Su, and Qin Lei Wei. "Research on Processing Conditions of CBS Transparent Glass-Ceramics." Advanced Materials Research 873 (December 2013): 733–36. http://dx.doi.org/10.4028/www.scientific.net/amr.873.733.
Divya, Dr R. "Human Eye Ball Gazing and Face Based Ultra Digital Security System using AI." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (April 30, 2024): 5643–48. http://dx.doi.org/10.22214/ijraset.2024.61295.
Nikolich, K., C. Sergides, and A. Pittas. "The application of near infrared reflectance spectroscopy (NIRS) for the quantitative analysis of hydrocortisone in primary materials." Journal of the Serbian Chemical Society 66, no. 3 (2001): 189–98. http://dx.doi.org/10.2298/jsc0103189n.
Porto López, Pablo. "Dibujar la realidad." Sur le journalisme, About journalism, Sobre jornalismo 12, no. 2 (December 22, 2023): 38–55. http://dx.doi.org/10.25200/slj.v12.n2.2023.579.
Dissertations / Theses on the topic "Verification de visage":
Hmani, Mohamed Amine. "Use of Biometrics for the Regeneration of Revocable Crypto-biometric Keys." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS013.
This thesis aims to regenerate crypto-biometric keys (cryptographic keys obtained with biometric data) that are resistant to quantum cryptanalysis methods. The challenge is to obtain keys with high entropy to have a high level of security, knowing that the entropy contained in biometric references limits the entropy of the key. Our choice was to exploit facial biometrics.We first created a state-of-the-art face recognition system based on public frameworks and publicly available data based on DNN embedding extractor architecture and triplet loss function. We participated in two H2020 projects. For the SpeechXRays project, we provided implementations of classical and cancelable face biometrics. For the H2020 EMPATHIC project, we created a face verification REST API. We also participated in the NIST SRE19 multimedia challenge with the final version of our classical face recognition system.In order to obtain crypto-biometric keys, it is necessary to have binary biometric references. To obtain the binary representations directly from face images, we proposed an original method, leveraging autoencoders and the previously implemented classical face biometrics. We also exploited the binary representations to create a cancelable face verification system.Regarding our final goal, to generate crypto-biometric keys, we focused on symmetric keys. Symmetric encryption is threatened by the Groover algorithm because it reduces the complexity of a brute force attack on a symmetric key from 2N à 2(N/2). To mitigate the risk introduced by quantum computing, we need to increase the size of the keys. To this end, we tried to make the binary representation longer and more discriminative. For the keys to be resistant to quantum computing, they should have double the length.We succeeded in regenerating crypto-biometric keys longer than 400bits (with low false acceptance and false rejection rates) thanks to the quality of the binary embeddings. The crypto-biometric keys have high entropy and are resistant to quantum cryptanalysis, according to the PQCrypto project, as they satisfy the length requirement. The keys are regenerated using a fuzzy commitment scheme leveraging BCH codes
Guillaumin, Matthieu. "Données multimodales pour l'analyse d'image." Phd thesis, Grenoble, 2010. http://www.theses.fr/2010GRENM048.
This dissertation delves into the use of textual metadata for image understanding. We seek to exploit this additional textual information as weak supervision to improve the learning of recognition models. There is a recent and growing interest for methods that exploit such data because they can potentially alleviate the need for manual annotation, which is a costly and time-consuming process. We focus on two types of visual data with associated textual information. First, we exploit news images that come with descriptive captions to address several face related tasks, including face verification, which is the task of deciding whether two images depict the same individual, and face naming, the problem of associating faces in a data set to their correct names. Second, we consider data consisting of images with user tags. We explore models for automatically predicting tags for new images, i. E. Image auto-annotation, which can also used for keyword-based image search. We also study a multimodal semi-supervised learning scenario for image categorisation. In this setting, the tags are assumed to be present in both labelled and unlabelled training data, while they are absent from the test data. Our work builds on the observation that most of these tasks can be solved if perfectly adequate similarity measures are used. We therefore introduce novel approaches that involve metric learning, nearest neighbour models and graph-based methods to learn, from the visual and textual data, task-specific similarities. For faces, our similarities focus on the identities of the individuals while, for images, they address more general semantic visual concepts. Experimentally, our approaches achieve state-of-the-art results on several standard and challenging data sets. On both types of data, we clearly show that learning using additional textual information improves the performance of visual recognition systems
Guillaumin, Matthieu. "Données multimodales pour l'analyse d'image." Phd thesis, Grenoble, 2010. http://tel.archives-ouvertes.fr/tel-00522278/en/.
Kučerová, Petra. "Analýza vybraných platebních protokolů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237207.
Visagie, Herman. "Evaluation and verification of an architecture suitable for a multi-unit control room of a pebble bed high temperature reactor nuclear power plant / Herman Visagie." Thesis, 2015. http://hdl.handle.net/10394/15761.
MIng (Nuclear Engineering), North-West University, Potchefstroom Campus, 2015
Books on the topic "Verification de visage":
Majumdar, Anindita. The Reproductive State. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199474363.003.0005.
Book chapters on the topic "Verification de visage":
Stavropoulos, Panagiotis, Dimitris Manitaras, Christos Papaioannou, Thanassis Souflas, and Harry Bikas. "Development of a Sensor Integrated Machining Vice Towards a Non-invasive Milling Monitoring System." In Lecture Notes in Mechanical Engineering, 29–37. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18326-3_3.
Conference papers on the topic "Verification de visage":
Sadeghi, Fereshteh, Santosh K. Divvala, and Ali Farhadi. "VisKE: Visual knowledge extraction and question answering by visual verification of relation phrases." In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2015. http://dx.doi.org/10.1109/cvpr.2015.7298752.
Echave, Javier, and Jami J. Shah. "Automatic Set-up and Fixture Planning for 3-Axis Milling." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/dac-8571.
Shadley, J. R., E. F. Rybicki, Y. Xiong, R. T. R. McGrann, and A. C. Savarimuthu. "An ASM Recommended Practice for Evaluation of Young’s Modulus and Poisson’s Ratio of Thermal Spray Coatings Bonded to a Substrate." In ITSC 2000, edited by Christopher C. Berndt. ASM International, 2000. http://dx.doi.org/10.31399/asm.cp.itsc2000p1291.