Literatura científica selecionada sobre o tema "Adaptation de domaines"
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Artigos de revistas sobre o assunto "Adaptation de domaines"
Nyeck, Simon, Sylvie Paradis, Jean-Marc Xuereb e Jean-Charles Chebat. "Standardisation ou adaptation des échelles de mesure à travers différents contextes nationaux: L'exemple d'une échelle de mesure de l'innovativité". Recherche et Applications en Marketing (French Edition) 11, n.º 3 (setembro de 1996): 57–74. http://dx.doi.org/10.1177/076737019601100304.
Texto completo da fonteLemire, Colombe, Carmen Dionne e Suzie McKinnon. "Accord interjuges des nouveaux domaines, la littératie et la numératie, de l’AEPS/EIS". Revue de psychoéducation 44, n.º 1 (3 de abril de 2017): 63–81. http://dx.doi.org/10.7202/1039271ar.
Texto completo da fonteDesseilles, Martin. "Adaptation et neurosciences I : craintes, société, méthodologie, finalité". Mosaïque 40, n.º 3 (29 de janeiro de 2016): 209–21. http://dx.doi.org/10.7202/1034919ar.
Texto completo da fonteDonon, Marlène. "Stabilité, changements et rythmes d’innovation du latin au français". SHS Web of Conferences 191 (2024): 03007. http://dx.doi.org/10.1051/shsconf/202419103007.
Texto completo da fonteBoutard, Guillaume. "À propos du Centre interdisciplinaire de recherche en musique, médias et technologie (cirmmt) : entretien avec Marcelo Wanderley". Circuit 24, n.º 2 (13 de agosto de 2014): 31–39. http://dx.doi.org/10.7202/1026182ar.
Texto completo da fonteNgom, Papa Ibrahima, Pascaline Attebi, Joseph Samba Diouf, Khady Diop Ba, Alpha Badiane e Falou Diagne. "Traduction et adaptation culturelle en français d’un indicateur de qualité de vie liée aux dysmorphoses orthodontiques : le PIDAQ". L'Orthodontie Française 84, n.º 4 (27 de novembro de 2013): 319–31. http://dx.doi.org/10.1051/orthodfr/2013066.
Texto completo da fonteSchmitt, Olivier. "La France : une puissance militaire à l’heure des choix". Questions internationales 119-120, n.º 3 (19 de outubro de 2023): 30–39. http://dx.doi.org/10.3917/quin.119.0030.
Texto completo da fontePaulet Dubois, Françoise. "extrême dans "La maison" de Julien Gracq, une lettre de Mme de Sévigné, un extrait de "Don Quijote" de Cervantès et de son adaptation par Florian". Cuadernos de Investigación Filológica 55 (30 de julho de 2024): 77–93. http://dx.doi.org/10.18172/cif.6069.
Texto completo da fonteLareau, André. "Réflexions fiscales sur la famille". Les Cahiers de droit 34, n.º 4 (12 de abril de 2005): 1205–34. http://dx.doi.org/10.7202/043249ar.
Texto completo da fonteSTAVILA AMARANDEI, R., S. MAHUT, P. SIXOU e A. JAMI. "Le patient, le médecin et la confiance : traduction, adaptation culturelle et validation de l'échelle de confiance de Wake Forest". EXERCER 32, n.º 176 (1 de outubro de 2021): 359–64. http://dx.doi.org/10.56746/exercer.2021.176.359.
Texto completo da fonteTeses / dissertações sobre o assunto "Adaptation de domaines"
Fernandes, Montesuma Eduardo. "Multi-Source Domain Adaptation through Wasserstein Barycenters". Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG045.
Texto completo da fonteMachine learning systems work under the assumption that training and test conditions are uniform, i.e., they do not change. However, this hypothesis is seldom met in practice. Hence, the system is trained with data that is no longer representative of the data it will be tested on. This case is represented by a shift in the probability measure generating the data. This scenario is known in the literature as distributional shift between two domains: a source, and a target. A straightforward generalization of this problem is when training data itself exhibit shifts on its own. In this case, one consider Multi Source Domain Adaptation (MSDA). In this context, optimal transport is an useful field of mathematics. Especially, optimal transport serves as a toolbox, for comparing and manipulating probability measures. This thesis studies the contributions of optimal transport to multi-source domain adaptation. We do so through Wasserstein barycenters, an object that defines a weighted average, in the space of probability measures, for the multiple domains in MSDA. Based on this concept, we propose: (i) a novel notion of barycenter, when the measures at hand are equipped with labels, (ii) a novel dictionary learning problem over empirical probability measures and (iii) new tools for domain adaptation through the optimal transport of Gaussian mixture models. Through our methods, we are able to improve domain adaptation performance in comparison with previous optimal transport-based methods on image, and cross-domain fault diagnosis benchmarks. Our work opens an interesting research direction, on learning the barycentric hull of probability measures
Lévesque-Gravel, Anick. "Adaptation de la formule de Schwarz-Christoffel aux domaines multiplement connexes". Master's thesis, Université Laval, 2015. http://hdl.handle.net/20.500.11794/26169.
Texto completo da fonteLa formule de Schwarz–Christoffel permet de trouver une transformation conforme entre un domaine polygonal et un disque. Par contre, cette formule ne s’applique qu’aux domaines simplement connexes. Récemment, Darren Crowdy a obtenu une généralisation de cette formule pour les domaines multiplement connexes. Celle-ci envoie des domaines circulaires sur des domaines polygonaux. Ce mémoire vise à faire la démonstration de la formule développée par Crowdy. Pour ce faire, il faudra définir la fonction de Schottky–Klein ainsi que la fonction de Green modifiée. Il faudra aussi introduire les domaines canoniques.
Meftah, Sara. "Neural Transfer Learning for Domain Adaptation in Natural Language Processing". Thesis, université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG021.
Texto completo da fonteRecent approaches based on end-to-end deep neural networks have revolutionised Natural Language Processing (NLP), achieving remarkable results in several tasks and languages. Nevertheless, these approaches are limited with their "gluttony" in terms of annotated data, since they rely on a supervised training paradigm, i.e. training from scratch on large amounts of annotated data. Therefore, there is a wide gap between NLP technologies capabilities for high-resource languages compared to the long tail of low-resourced languages. Moreover, NLP researchers have focused much of their effort on training NLP models on the news domain, due to the availability of training data. However, many research works have highlighted that models trained on news fail to work efficiently on out-of-domain data, due to their lack of robustness against domain shifts. This thesis presents a study of transfer learning approaches, through which we propose different methods to take benefit from the pre-learned knowledge on the high-resourced domain to enhance the performance of neural NLP models in low-resourced settings. Precisely, we apply our approaches to transfer from the news domain to the social media domain. Indeed, despite the importance of its valuable content for a variety of applications (e.g. public security, health monitoring, or trends highlight), this domain is still poor in terms of annotated data. We present different contributions. First, we propose two methods to transfer the knowledge encoded in the neural representations of a source model pretrained on large labelled datasets from the source domain to the target model, further adapted by a fine-tuning on few annotated examples from the target domain. The first transfers contextualised supervisedly pretrained representations, while the second method transfers pretrained weights, used to initialise the target model's parameters. Second, we perform a series of analysis to spot the limits of the above-mentioned proposed methods. We find that even if the proposed transfer learning approach enhances the performance on social media domain, a hidden negative transfer may mitigate the final gain brought by transfer learning. In addition, an interpretive analysis of the pretrained model, show that pretrained neurons may be biased by what they have learned from the source domain, thus struggle with learning uncommon target-specific patterns. Third, stemming from our analysis, we propose a new adaptation scheme which augments the target model with normalised, weighted and randomly initialised neurons that beget a better adaptation while maintaining the valuable source knowledge. Finally, we propose a model, that in addition to the pre-learned knowledge from the high-resource source-domain, takes advantage of various supervised NLP tasks
Marchand, Morgane. "Domaines et fouille d'opinion : une étude des marqueurs multi-polaires au niveau du texte". Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112026/document.
Texto completo da fonteIn this thesis, we are studying the adaptation of a text level opinion classifier across domains. Howerver, people express their opinion in a different way depending on the subject of the conversation. The same word in two different domains can refer to different objects or have an other connotation. If these words are not detected, they will lead to classification errors.We call these words or bigrams « multi-polarity marquers ». Their presence in a text signals a polarity wich is different according to the domain of the text. Their study is the subject of this thesis. These marquers are detected using a khi2 test if labels exist in both targeted domains. We also propose a semi-supervised detection method for the case with labels in only one domain. We use a collection of auto-epurated pivot words in order to assure a stable polarity accross domains.We have also checked the linguistic interest of the selected words with a manual evaluation campaign. The validated words can be : a word of context, a word giving an opinion, a word explaining an opinion or a word wich refer to the evaluated object. Our study also show that the causes of the changing polarity are of three kinds : changing meaning, changing object or changing use.Finally, we have studyed the influence of multi-polarity marquers on opinion classification at text level in three different cases : adaptation of a source domain to a target domain, multi-domain corpora and open domain corpora. The results of our experiments show that the potential improvement is bigger when the initial transfer was difficult. In the favorable cases, we improve accurracy up to five points
Passerieux, Emilie. "Corrélation entre l'organisation spatiale du perimysium et des domaines subcellulaires des fibres musculaires squelettiques : implication dans la transmission latérale des forces et conséquences possibles sur les adaptations du muscle à l'exercice physique". Bordeaux 2, 2006. http://www.theses.fr/2006BOR21358.
Texto completo da fonteWe investigated the possibility that the perimysium, a component of intramuscular connective tissue, is involved in muscular adaptation mechanisms. We demonstrated in bovine skeletal Flexor carpi radialis muscle that (i) the perimysium drives the forces of muscular contraction from myofibers to the tendons, (ii) the spatial distribution of the perimysium in muscle corresponds directly to the distribution of integrins (associated with the presence of satellite cells at the surface of myofibers) and the distribution of myonuclei, subsarcolemmal mitochondria, and myosin inside myofibers. We concluded that the perimysium-myofiber relationship reflects the existence of a mechanosensor system explaining short and long term muscle adaptations. Our investigations were essential for detecting the way of myofibers adaptations
Delaforge, Elise. "Dynamique structurale et fonctionnelle du domaine C-terminal de la protéine PB2 du virus de la grippe A". Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAV037/document.
Texto completo da fonteThe ability of avian influenza viruses to cross the species barrier and become dangerously pathogenic to mammalian hosts represents a major threat for human health. In birds the viral replication is carried out in the intestine at 40°C, while in humans it occurs in the cooler respiratory tract at 33°C. It has been shown that temperature adaption of the influenza virus occurs through numerous mutations in the viral polymerase, in particular in the C-terminal domain 627-NLS of the PB2 protein. This domain has already been shown to participate in host adaptation and is involved in importin alpha binding and therefore is required for entry of the viral polymerase into the nucleus [Tarendeau et al., 2008]. Crystallographic structures are available for 627-NLS and the complex importin alpha/NLS, however, a steric clash between importin alpha and the 627 domain becomes apparent when superimposing the NLS domain of the two structures, indicating that another conformation of 627-NLS is required for binding to importin alpha [Boivin and Hart, 2011]. Here we investigate the molecular basis of inter-species adaptation by studying the structure and dynamics of human and avian 627-NLS. We have identified two conformations of 627-NLS in slow exchange (10-100 s-1), corresponding to an apparently open and closed conformation of the two domains. We show that the equilibrium between closed and open conformations is strongly temperature dependent. We propose that the open conformation of 627-NLS is the only conformation compatible with binding to importin alpha and that the equilibrium between closed and open conformations may play a role as a molecular thermostat, controlling the efficiency of viral replication in the different species. The kinetics and domain dynamics of this important conformational behaviour and of the interaction between 627-NLS and importin alpha have been characterized using nuclear magnetic resonance chemical shifts, paramagnetic relaxation enhancement, spin relaxation and chemical exchange saturation transfer, in combination with X-ray and neutron small angle scattering and Förster resonance energy transfer. Also, we have determined the affinities of various evolutionnary mutants of 627-NLS to importin alpha and of avian and human 627-NLS to different isoforms of importin alpha, showing that the observed affinities are coherent with the preferred interactions seen in vivo
Lopez, Rémy. "Adaptation des méthodes “statistical energy analysis” (sea) aux problèmes d'électromagnétisme en cavités". Toulouse 3, 2006. http://www.theses.fr/2006TOU30045.
Texto completo da fonteModeling electromagnetic phenomena by deterministic methods requires a subdivision of the volume under study into a number of discrete elements with sizes of the order of tenth of the wavelength. So, the demand for computer resources significantly grows with increasing frequencies. Moreover, taking into account the complexity of the problems and the uncertainties on the input data, it becomes illusory to make a deterministic calculation for each studied variable. New methods, called energetic methods, were developed to study systems large in front of the wavelength. They allow to estimate statistically the value of the field inside a system One of these methods, the Statistical Energy Analysis (SEA), developed in acoustic, is transposed here in electromagnetism. The SEA allows to describe the exchanges of energy between the different systems of a structure. The energy of each system depends on the concepts of mode of resonance, loss and coupling. The parameters linked with these concepts are assessed by analytical formulae and numerical simulations. An automatic sub structuring method is also presented. The results obtained seem to confirm the interest of this method
Sidibe, Mamadou Gouro. "Métrologie des services audiovisuels dans un contexte multi-opérateurs et multi-domaines réseaux". Versailles-St Quentin en Yvelines, 2010. http://www.theses.fr/2010VERS0068.
Texto completo da fonteAccess to multimedia services over heterogeneous networks and terminals is of increasing market interest, while providing end-to-end (E2E) Quality of Service (QoS) guarantees is still a challenge. Solving this issue requires to deploy new E2E management architectures including components that monitor the network QoS (NQoS) parameters, as well as the Quality of Experience (QoE) of the user. In this thesis, we first propose an E2E Integrated QoS Management Supervisor for an efficient provisioning, monitoring and adaptation of video services using the MPEG-21 standard. We then propose a novel QoE-aware monitoring solution for large-scale service connectivity and user-perceived quality monitoring over heterogeneous networks. The solution specifies a scalable cross-layer monitoring architecture, comprising four types of QoS monitoring agents operating at node, network, application and service levels. It also specifies related intra/inter-domain signalling protocols
Rouquet, Géraldine. "Etude du rôle de l'opéron métabolique frz dans la virulence d'escherichia coli et dans son adaptation aux conditions environnementales". Thesis, Tours, 2010. http://www.theses.fr/2010TOUR4008.
Texto completo da fonteThe metabolic frz operon codes for three subunits of a PTS transporter of the fructose sub-family, for a transcriptional activator of PTS systems of the MgA family (FrzR), for two type II ketose-1,6-bisphosphate aldolases, for a sugar specific kinase (ROK family) and for a protein of the cupin superfamily. It is highly associated with Extra-intestinal Pathogenic Escherichia coli strains. We proved that frz promotes bacterial fitness under stressful conditions, (such as oxygen restriction, late stationary phase of growth or growth in serum or in the intestinal tract). Furthermore, we showed that frz is involved in adherence to and internalization of E. coli in several eukaryotic cells by regulating the expression of type 1 fimbriae. The FrzR activator is involved in these phenotypes. Microarrays, experiments allowed the identification of several genes under the dependence of the frz system. Our data suggest that frz codes for a sensor of the environment allowing E. coli to adapt to a fluctuating environment by regulating some virulence and host adaptation genes. A regulation model is presented
Alqasir, Hiba. "Apprentissage profond pour l'analyse de scènes de remontées mécaniques : amélioration de la généralisation dans un contexte multi-domaines". Thesis, Lyon, 2020. http://www.theses.fr/2020LYSES045.
Texto completo da fonteThis thesis presents our work on chairlift safety using deep learning techniques as part of the Mivao project, which aims to develop a computer vision system that acquires images of the chairlift boarding station, analyzes the crucial elements, and detects dangerous situations. In this scenario, we have different chairlifts spread over different ski resorts, with a high diversity of acquisition conditions and geometries; thus, each chairlift is considered a domain. When the system is installed for a new chairlift, the objective is to perform an accurate and reliable scene analysis, given the lack of labeled data on this new domain (chairlift).In this context, we mainly concentrate on the chairlift safety bar and propose to classify each image into two categories, depending on whether the safety bar is closed (safe) or open (unsafe). Thus, it is an image classification problem with three specific features: (i) the image category depends on a small detail (the safety bar) in a cluttered background, (ii) manual annotations are not easy to obtain, (iii) a classifier trained on some chairlifts should provide good results on a new one (generalization). To guide the classifier towards the important regions of the images, we have proposed two solutions: object detection and Siamese networks. Furthermore, we analyzed the generalization property of these two approaches. Our solutions are motivated by the need to minimize human annotation efforts while improving the accuracy of the chairlift safety problem. However, these contributions are not necessarily limited to this specific application context, and they may be applied to other problems in a multi-domain context
Livros sobre o assunto "Adaptation de domaines"
Li, Jingjing, Lei Zhu e Zhekai Du. Unsupervised Domain Adaptation. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6.
Texto completo da fonteKamnitsas, Konstantinos, Lisa Koch, Mobarakol Islam, Ziyue Xu, Jorge Cardoso, Qi Dou, Nicola Rieke e Sotirios Tsaftaris, eds. Domain Adaptation and Representation Transfer. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16852-9.
Texto completo da fonteSingh, Richa, Mayank Vatsa, Vishal M. Patel e Nalini Ratha, eds. Domain Adaptation for Visual Understanding. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-30671-7.
Texto completo da fonteKoch, Lisa, M. Jorge Cardoso, Enzo Ferrante, Konstantinos Kamnitsas, Mobarakol Islam, Meirui Jiang, Nicola Rieke, Sotirios A. Tsaftaris e Dong Yang, eds. Domain Adaptation and Representation Transfer. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-45857-6.
Texto completo da fonteCsurka, Gabriela, ed. Domain Adaptation in Computer Vision Applications. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58347-1.
Texto completo da fonteCsurka, Gabriela, Timothy M. Hospedales, Mathieu Salzmann e Tatiana Tommasi. Visual Domain Adaptation in the Deep Learning Era. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-79175-8.
Texto completo da fonteVenkateswara, Hemanth, e Sethuraman Panchanathan, eds. Domain Adaptation in Computer Vision with Deep Learning. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45529-3.
Texto completo da fonteSøgaard, Anders. Semi-Supervised Learning and Domain Adaptation in Natural Language Processing. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-031-02149-7.
Texto completo da fonteAlbarqouni, Shadi, Spyridon Bakas, Konstantinos Kamnitsas, M. Jorge Cardoso, Bennett Landman, Wenqi Li, Fausto Milletari et al., eds. Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60548-3.
Texto completo da fonteBunt, Harry C. Trends in Parsing Technology: Dependency Parsing, Domain Adaptation, and Deep Parsing. Dordrecht: Springer Science+Business Media B.V., 2011.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Adaptation de domaines"
Hoffman, Judy, Brian Kulis, Trevor Darrell e Kate Saenko. "Discovering Latent Domains for Multisource Domain Adaptation". In Computer Vision – ECCV 2012, 702–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33709-3_50.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Introduction to Domain Adaptation". In Unsupervised Domain Adaptation, 1–6. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_1.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Unsupervised Domain Adaptation Techniques". In Unsupervised Domain Adaptation, 7–17. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_2.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Continual Test-Time Unsupervised Domain Adaptation". In Unsupervised Domain Adaptation, 191–212. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_7.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Applications". In Unsupervised Domain Adaptation, 213–18. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_8.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Criterion Optimization-Based Unsupervised Domain Adaptation". In Unsupervised Domain Adaptation, 19–67. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_3.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Bi-Classifier Adversarial Learning-Based Unsupervised Domain Adaptation". In Unsupervised Domain Adaptation, 69–104. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_4.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Active Learning for Unsupervised Domain Adaptation". In Unsupervised Domain Adaptation, 139–89. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_6.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Source-Free Unsupervised Domain Adaptation". In Unsupervised Domain Adaptation, 105–37. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_5.
Texto completo da fonteLi, Jingjing, Lei Zhu e Zhekai Du. "Research Frontier". In Unsupervised Domain Adaptation, 219–23. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1025-6_9.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Adaptation de domaines"
Wang, Zengmao, Chaoyang Zhou, Bo Du e Fengxiang He. "Self-paced Supervision for Multi-source Domain Adaptation". In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/493.
Texto completo da fonteWu, Keyu, Min Wu, Jianfei Yang, Zhenghua Chen, Zhengguo Li e Xiaoli Li. "Deep Reinforcement Learning Boosted Partial Domain Adaptation". In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/439.
Texto completo da fonteMancini, Massimiliano, Lorenzo Porzi, Samuel Rota Bulo, Barbara Caputo e Elisa Ricci. "Boosting Domain Adaptation by Discovering Latent Domains". In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2018. http://dx.doi.org/10.1109/cvpr.2018.00397.
Texto completo da fonteĆiprijanović, Aleksandra, Diana Kafkes, Sydney Jenkins, K. Downey, Gabriel Perdue, S. Madireddy, T. Johnston e Brian Nord. "Domain Adaptation for Cross-Domain Studies of Merging Galaxies". In Domain Adaptation for Cross-Domain Studies of Merging Galaxies. US DOE, 2021. http://dx.doi.org/10.2172/1825309.
Texto completo da fonteQin, Xiaoli, e William C. Regli. "Applying Case-Based Reasoning to Mechanical Bearing Design". In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/dfm-14011.
Texto completo da fonteYan, Zizheng, Yushuang Wu, Guanbin Li, Yipeng Qin, Xiaoguang Han e Shuguang Cui. "Multi-level Consistency Learning for Semi-supervised Domain Adaptation". In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/213.
Texto completo da fonteXu, Rongtao, Changwei Wang, Bin Fan, Yuyang Zhang, Shibiao Xu, Weiliang Meng e Xiaopeng Zhang. "DOMAINDESC: Learning Local Descriptors With Domain Adaptation". In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9747786.
Texto completo da fonteWen, Jun, Nenggan Zheng, Junsong Yuan, Zhefeng Gong e Changyou Chen. "Bayesian Uncertainty Matching for Unsupervised Domain Adaptation". In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/534.
Texto completo da fonteĆiprijanović, Aleksandra. "Domain Adaptation for Cross-Domain Studies in Astronomy: Merging Galaxies Identification". In Domain Adaptation for Cross-Domain Studies in Astronomy: Merging Galaxies Identification. US DOE, 2021. http://dx.doi.org/10.2172/1827857.
Texto completo da fonteAlvarenga e Silva, Lucas Fernando, e Jurandy Almeida. "MS-DIAL: Multi-Source Domain Alignment Layers for Unsupervised Domain Adaptation". In Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/wvc.2020.13490.
Texto completo da fonteRelatórios de organizações sobre o assunto "Adaptation de domaines"
Lei, Xin, Wen Wang e Andreas Stolcke. Unsupervised Domain Adaptation with Multiple Acoustic Models. Fort Belvoir, VA: Defense Technical Information Center, dezembro de 2010. http://dx.doi.org/10.21236/ada630345.
Texto completo da fonteRussell, H. A. J., e S. K. Frey. Canada One Water: integrated groundwater-surface-water-climate modelling for climate change adaptation. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329092.
Texto completo da fonteMukherjee, Amitangshu. Semantic Domain Adaptation for Deep Networks via GAN-based Data Augmentation for Autonomous Driving. Ames (Iowa): Iowa State University, janeiro de 2019. http://dx.doi.org/10.31274/cc-20240624-1273.
Texto completo da fonteChristopher, David A., e Avihai Danon. Plant Adaptation to Light Stress: Genetic Regulatory Mechanisms. United States Department of Agriculture, maio de 2004. http://dx.doi.org/10.32747/2004.7586534.bard.
Texto completo da fonteVilalta, Ricardo. Modern Machine Learning Techniques. Instats Inc., 2024. http://dx.doi.org/10.61700/6sziq6usb3koe786.
Texto completo da fonteWarren, Nancy, Pia Mingkwan, Caroline Kery, Meagan Meekins, Thomas Bukowski e Laura Nyblade. Identifying and Classifying COVID-19 Stigma on Social Media. RTI Press, maio de 2023. http://dx.doi.org/10.3768/rtipress.2023.op.0087.2305.
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