Littérature scientifique sur le sujet « NeuralRTI »
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Articles de revues sur le sujet "NeuralRTI"
Dulecha, Tinsae G., Filippo A. Fanni, Federico Ponchio, Fabio Pellacini et Andrea Giachetti. « Neural reflectance transformation imaging ». Visual Computer 36, no 10-12 (17 juillet 2020) : 2161–74. http://dx.doi.org/10.1007/s00371-020-01910-9.
Texte intégralWu, Robert, Nayan Saxena et Rohan Jain. « NeuralArTS : Structuring Neural Architecture Search with Type Theory (Student Abstract) ». Proceedings of the AAAI Conference on Artificial Intelligence 36, no 11 (28 juin 2022) : 13085–86. http://dx.doi.org/10.1609/aaai.v36i11.21679.
Texte intégralMichalska-Bańkowska, Anna, Anna Lis-Święty, Mirosław Bańkowski et Agata Zielonka-Kucharzewska. « Prophylaxis and treatment of acute and chronic postherpetic neuralgia ». Dermatology Review 3 (2014) : 205–10. http://dx.doi.org/10.5114/dr.2014.43812.
Texte intégralCapecchi, Vittorio. « Matematica e sociologia. Da Lazarsfeld alle reti neurali artificiali ». SOCIOLOGIA E RICERCA SOCIALE, no 87 (mai 2009) : 5–90. http://dx.doi.org/10.3280/sr2008-087001.
Texte intégralAglioti, Salvatore Maria, et Ilaria Bufalari. « Trasformare le rappresentazioni mentali e neurali del corpo e del sé ». RIVISTA SPERIMENTALE DI FRENIATRIA, no 1 (mars 2015) : 113–28. http://dx.doi.org/10.3280/rsf2015-001009.
Texte intégralCooper, Steven H. « Interpretive Fallibility and the Psychoanalytic Dialogue ». Journal of the American Psychoanalytic Association 41, no 1 (mars 1993) : 95–126. http://dx.doi.org/10.1177/000306519304100104.
Texte intégralPescia, Lorenza. « La femminilizzazione degli agentivi nell’era digitale : la rappresentazione linguistica delle donne e google translate ». Babylonia Journal of Language Education 3 (20 décembre 2021) : 102–9. http://dx.doi.org/10.55393/babylonia.v3i.133.
Texte intégralKloc, Wojciech, Witold Libionka, Wojciech Skrobot et Krzysztof Basiński. « Neurochirurgiczne leczenie bólu– część II. Współczesne metody leczenia chirurgicznego neuralgii nerwu trójdzielnego i innych przewlekłych bólów twarzy ». Ból 16, no 4 (31 décembre 2015) : 43–50. http://dx.doi.org/10.5604/1640324x.1193857.
Texte intégralSekulić Sović, Martina, Vlasta Erdeljac et Hrvoje Hećimović. « Medijalni temporalni režanj kao neuralni korelat leksičko‐semantičke obrade apstraktnosti i konkretnosti kod osoba s epilepsijom ». Govor/Speech 33, no 1 (10 avril 2017) : 39–66. http://dx.doi.org/10.22210/govor.2016.33.02.
Texte intégralDecherchi, Carlo, et Pier Giuseppe Giribone. « Prospective estimate of financial risk measures through dynamic neural networks : an application to the U.S. market ». Risk Management Magazine 1, no 2020 (8 avril 2020) : 50–69. http://dx.doi.org/10.47473/2020rmm0008.
Texte intégralThèses sur le sujet "NeuralRTI"
Fabbri, Alessandro. « Reti neurali in ambito finanziario ». Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19593/.
Texte intégralKarlsteen, Joakim. « Fuskdetektion med artificiellt neuralt nätverk ». Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-20527.
Texte intégralDet finns övrigt digitalt material (t.ex. film-, bild- eller ljudfiler) eller modeller/artefakter tillhörande examensarbetet som ska skickas till arkivet.
Soncini, Filippo. « Classificazione di documenti tramite reti neurali ». Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20509/.
Texte intégralEklund, Björn. « Uppdelning av ett artificiellt neuralt nätverk ». Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5667.
Texte intégralCorazza, Michele. « Coreference Resoultion basata su reti neurali deep ». Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14554/.
Texte intégralVagnoni, Ulderico. « Analisi di immagini storiche con reti neurali ». Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19624/.
Texte intégralBrigandì, Camilla. « Utilizzo della omologia persistente nelle reti neurali ». Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2022.
Trouver le texte intégralNicklasson, Emma, et Erik Nyqvist. « Ansiktsautentiseringssystem med neuralt nätverk : Baserat på bildklassificering ». Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-84338.
Texte intégralFace recognition using machine learning is a changing field and is used in many contexts in today’s society, for example as an authentication method in mobile phones. Most face recognition systems have had large budgets and strong developers behind them, but is it possible to create a working system with a limited amount of resourses and data? This project investigates how much data is required to produce a working face recognition module for an office environment based on image classification. This project used a pretrained Convolutional Neural Network (ResNet34), data collected with the help of the client, and an image database from NVIDIA. The results show that the amount of data required to produce and reliable model probably exceeds the amount that is reasonable to collect from the user.
ZANCATO, LUCA. « Sull'addestrabilità e generalizzazione delle Reti Neurali Profonde ». Doctoral thesis, Università degli studi di Padova, 2022. http://hdl.handle.net/11577/3446030.
Texte intégralThe last few years have witnessed the rise of Deep Neural Networks. Since the introduction of AlexNet in 2012, the community of researchers and industries employing Deep Learning has exploded. This surge in attention led to the development of State of The Art algorithms in many different fields such as Computer Vision, Natural Language Processing and Time Series modeling. The empirical success of Deep Learning posed new methodological challenges for academia and allowed industry to deploy world-wide large scale web services unthinkable ten years ago. Despite such incontrovertible success, Deep Learning does not come free of issues: model design is highly costly, model interpretability is not easy, deployment often requires very specialized experts and, not least, any Deep Neural Network requires a large amount of data for training. Moreover, from a theoretical standpoint many important guarantees on optimization convergence and generalization are still lacking. In this thesis we address trainability and generalization of Deep Neural Network models: we analyze the optimization trajectories and the generalization of typical over-parametrized models; moreover, we design a specialized inductive bias and regularization scheme to foster interpretability and generalization of Deep Neural Networks. The starting point in our analysis is a recently proposed tool: the Neural Tangent Kernel for over-parametrized models. Building on this fundamental result, we investigate the number of optimization steps that a pre-trained Deep Neural Network needs to converge to a given value of the loss function ("Training Time"). Moreover, we exploit the Neural Tangent Kernel theory to solve the problem of choosing the best pre-trained Deep Neural Network within a "model zoo" when only the target dataset is known and without training any model ("Model Selection"). Our analysis started to unblock the adoption of real-world Computer Vision AutoML systems: Users fine-tune models selected from a large "model zoo" testing hundreds of combinations of different architectures, pre-training sets and hyper-parameters, but are reluctant to do so without an estimate of the expected training cost. Our results are a step towards better understanding of transfer learning through a novel study on the interplay between generalization and highly over-parametrized Deep Neural Networks. We then build a specialized Deep architecture equipped with a strong inductive bias and explicit regularization, that are designed both to constrain the representational power of our architecture and to allow Bayesian automatic complexity selection. Then, we show our novel method can be successfully applied both for non-linear System Identification and for Anomaly Detection of large scale Time Series.
Cino, G. « Implementazione ed analisi di reti neurali wetware ». Doctoral thesis, Università degli Studi di Milano, 2007. http://hdl.handle.net/2434/180804.
Texte intégralLivres sur le sujet "NeuralRTI"
Floreano, Dario. Manuale sulle reti neurali. 2e éd. Bologna : Il mulino, 2002.
Trouver le texte intégralCeschia, Mario. La previsione delle precipitazioni a scala mensile : Confronto tra modelli statistici e a reti neurali, il caso di Udine. Udine : Forum, 2000.
Trouver le texte intégralBuzzanca, Giuseppe. Musica e intelligenza artificiale : Per un modello connessionista di mente musicale, teoria dei linguaggi formali, reti neurali artificiali e relative applicazioni in informatica musicale. Bari : Florestano edizioni, 2016.
Trouver le texte intégralwilliam, Emma. Sviluppo Di Reti Neurali : Come Vengono Sviluppate le Reti Neurali ? Independently Published, 2022.
Trouver le texte intégralMarco, Tommaso. Evoluzione Delle Reti Neurali. Independently Published, 2022.
Trouver le texte intégralColecchia, Nicola. Neuroinformazioni : Campi Di Applicazione Delle Reti Neurali. Independently Published, 2017.
Trouver le texte intégralSisini, Francesco. Introduzione Alle Reti Neurali con Esempi in Linguaggio C. Independently Published, 2018.
Trouver le texte intégralSisini, Francesco. Introduzione Alle Reti Neurali con Esempi in Linguaggio C. Independently Published, 2019.
Trouver le texte intégralColecchia, Nicola. Cosa Sono I Neuroni Artificiali : Campi Di Applicazione Delle Reti Neurali. Independently Published, 2018.
Trouver le texte intégralSisini, Francesco, et Valentina Sisini. Reti Neurali Non Supervisionate : il Cognitrone Di Fukushima : Con Codice in Linguaggio C. Independently Published, 2019.
Trouver le texte intégralChapitres de livres sur le sujet "NeuralRTI"
D’Amato, Luca Colucci, et Umberto di Porzio. « Le cellule staminali neurali ». Dans Introduzione alla neurobiologia, 91–103. Milano : Springer Milan, 2011. http://dx.doi.org/10.1007/978-88-470-1944-7_7.
Texte intégralCascini, Giuseppe Lucio, Vincenzo Donato et Oscar Tamburrini. « Introduzione alle reti neurali ». Dans Elementi di informatica in diagnostica per immagini, 217–33. Milano : Springer Milan, 2010. http://dx.doi.org/10.1007/978-88-470-1667-5_18.
Texte intégralLi, Xuyang, Hamed Bolandi, Talal Salem, Nizar Lajnef et Vishnu Naresh Boddeti. « NeuralSI : Structural Parameter Identification in Nonlinear Dynamical Systems ». Dans Lecture Notes in Computer Science, 332–48. Cham : Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25082-8_22.
Texte intégralActes de conférences sur le sujet "NeuralRTI"
Castro Ferreira, Thiago, Diego Moussallem, Ákos Kádár, Sander Wubben et Emiel Krahmer. « NeuralREG : An end-to-end approach to referring expression generation ». Dans Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1 : Long Papers). Stroudsburg, PA, USA : Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/p18-1182.
Texte intégral« NEURALTB WEB SYSTEM - Support to the Smear Negative Pulmonary Tuberculosis Diagnosis ». Dans 9th International Conference on Enterprise Information Systems. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0002366401980203.
Texte intégralChen, Zhennong, Kunal Gupta et Francisco Contijoch. « Motion correction image reconstruction using NeuralCT improves with spatially aware object segmentation ». Dans Seventh International Conference on Image Formation in X-Ray Computed Tomography (ICIFXCT 2022), sous la direction de Joseph Webster Stayman. SPIE, 2022. http://dx.doi.org/10.1117/12.2646402.
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