Literatura académica sobre el tema "Novel class discovery"
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Artículos de revistas sobre el tema "Novel class discovery"
Chen, Guangyao, Peixi Peng, Yangru Huang, Mengyue Geng y Yonghong Tian. "Adaptive Discovering and Merging for Incremental Novel Class Discovery". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 10 (24 de marzo de 2024): 11276–84. http://dx.doi.org/10.1609/aaai.v38i10.29006.
Texto completoDandliker, Peter J., Steve D. Pratt, Angela M. Nilius, Candace Black-Schaefer, Xiaoan Ruan, Danli L. Towne, Richard F. Clark et al. "Novel Antibacterial Class". Antimicrobial Agents and Chemotherapy 47, n.º 12 (diciembre de 2003): 3831–39. http://dx.doi.org/10.1128/aac.47.12.3831-3839.2003.
Texto completoWang, Weishuai, Ting Lei, Qingchao Chen y Yang Liu. "Semantic-Guided Novel Category Discovery". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 6 (24 de marzo de 2024): 5607–14. http://dx.doi.org/10.1609/aaai.v38i6.28371.
Texto completoShinozuka, Tsuyoshi, Shuichiro Ito, Takako Kimura, Masanori Izumi y Kenji Wakabayashi. "Discovery of a Novel Class of ERRα Agonists". ACS Medicinal Chemistry Letters 12, n.º 5 (21 de abril de 2021): 817–21. http://dx.doi.org/10.1021/acsmedchemlett.1c00100.
Texto completoCubitt, Jonathan, Mari Davies, Ross Riseley, Gabrielle Evans, Sian E. Gardiner, Benson M. Kariuki, Simon E. Ward, Emyr Lloyd-Evans, Helen Waller-Evans y D. Heulyn Jones. "Beware of N-Benzoyloxybenzamides". Molecules 29, n.º 21 (31 de octubre de 2024): 5143. http://dx.doi.org/10.3390/molecules29215143.
Texto completoFeng, Juexiao, Yuhong Yang, Yanchun Xie, Yaqian Li, Yandong Guo, Yuchen Guo, Yuwei He, Liuyu Xiang y Guiguang Ding. "Debiased Novel Category Discovering and Localization". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 2 (24 de marzo de 2024): 1753–60. http://dx.doi.org/10.1609/aaai.v38i2.27943.
Texto completoShearer, Barry G., Hari S. Patel, Andrew N. Billin, James M. Way, Deborah A. Winegar, Millard H. Lambert, Robert X. Xu et al. "Discovery of a novel class of PPARδ partial agonists". Bioorganic & Medicinal Chemistry Letters 18, n.º 18 (septiembre de 2008): 5018–22. http://dx.doi.org/10.1016/j.bmcl.2008.08.011.
Texto completoCheleski, Juliana, Josmar R. Rocha, Matheus P. Pinheiro, Helton José Wiggers, Albérico B. F. da Silva, Maria C. Nonato y Carlos A. Montanari. "Novel insights for dihydroorotate dehydrogenase class 1A inhibitors discovery". European Journal of Medicinal Chemistry 45, n.º 12 (diciembre de 2010): 5899–909. http://dx.doi.org/10.1016/j.ejmech.2010.09.055.
Texto completoFukunaga, Alex S. "Automated Discovery of Local Search Heuristics for Satisfiability Testing". Evolutionary Computation 16, n.º 1 (marzo de 2008): 31–61. http://dx.doi.org/10.1162/evco.2008.16.1.31.
Texto completoHilgeroth, Andreas, Marc Hemmer, Sebastian Neuber, Josef Molnar y Hermann Lage. "Discovery of 9,10-Dihydroacridines as Novel Class of ABCB1 Inhibitors". Medicinal Chemistry 11, n.º 4 (29 de abril de 2015): 329–35. http://dx.doi.org/10.2174/1573406410666141111100720.
Texto completoTesis sobre el tema "Novel class discovery"
Troisemaine, Colin. "Novel class discovery in tabular data : an application to network fault diagnosis". Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2024. http://www.theses.fr/2024IMTA0422.
Texto completoThis thesis focuses on Novel Class Discovery (NCD) in the context of tabular data. The Novel Class Discovery problem consists in extracting knowledge from a labeled set of already known classes in order to more accurately partition an unlabeled set of new classes. Although NCD has recently received a lot of of attention from the community, it is generally addressed in computer vision problems and sometimes under unrealistic conditions. In particular, the number of novel classes is often assumed to be known in advance, and their labels are sometimes used to tune hyperparameters. Methods based on these assumptions are not applicable to realworld scenarios. Thus, in this thesis we focus on discovery resolution in tabular data when no a priori knowledge is available. The methods developed in the thesis are applied to a real-world case: automatic fault diagnosis in telecommunication networks, with a focus on fiber optic access networks. The aim is to achieve efficient fault management, particularly at the diagnosis stage when unknown faults (new classes) may appear
Ordway, Gregory A. "Discovery of a New Biological Target for the Development of a Novel Class of Antidepressant Drugs". Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/8655.
Texto completoParker, Mackenzie James. "Discovery and investigation of the novel overall activity allosteric regulation of the Bacillus subtilis class Ib ribonucleotide reductase". Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/109681.
Texto completoPage 490 blank. Cataloged from PDF version of thesis.
Includes bibliographical references.
Ribonucleotide reductases (RNRs) catalyze the reduction of nucleotides to 2'-deoxynucleotides in all organisms. Class lb RNRs consist of two subunits: a houses the catalytic and allosteric effector binding sites, and p houses a catalytically essential dimanganic-tyrosyl radical (Mn(III)2-Y*). The allosteric regulation of lb RNR activity has only been studied with the Salmonella enterica enzyme, which exhibits substrate specificity allosteric regulation by ATP and 2'-deoxynucleoside 5'-triphosphates (dNTPs), but not overall activity regulation by ATP and dATP. However, the S. enterica enzyme is not a good general model for Ib RNRs because it is not essential under most growth conditions, including pathogenesis. Other bacteria pathogenic to humans utilize lb RNRs as their sole source of dNTPs for DNA replication and repair. As RNR regulation plays a critical role in the high fidelity of these processes, the allosteric regulation of lb RNRs used as the primary dNTP supplier for a bacterium should be distinct from the S. enterica enzyme and, therefore, could provide a potential target for therapeutic development. Herein, the results of characterizing the allosteric regulation of the Ib RNR from the model organism Bacillus subtilis are presented. To facilitate these studies, we identified, cloned, and isolated the physiological reductant for RNR (thioredoxin/thioredoxin reductase/NADPH), thus allowing us to monitor activity spectrophotometrically. We discovered the effector dATP was a potent inhibitor of enzymatic activity at physiologically relevant concentrations, thereby demonstrating the first example of overall activity allosteric regulation in a class lb system. In other RNRs, overall activity regulation is mediated by a domain called the ATP-cone. This domain is absent from the B. subtilis enzyme; therefore, the inhibition represents a new mechanism of overall activity regulation. Analytical ultracentrifugation studies suggest dATP inhibition may be mediated by formation of large protein complexes. Biophysical studies also led to the discovery of tightly bound dAMP associated with a that increases the susceptibility of RNR to dATP inhibition. The potential physiological importance of dAMP is supported by studies examining YmaB, the unique fourth member of the B. subtilis RNR operon, which revealed this enzyme can hydrolyze dATP into dAMP and pyrophosphate and, therefore, might insert dAMP into a.
by Mackenzie James Parker.
Ph. D.
Libros sobre el tema "Novel class discovery"
Stanton, Benjamin Z. Discovery and mechanistic characterization of a novel class of sonic hedgehog inhibitors. 2009.
Buscar texto completoYang, Jimmy Chen. Discovery, synthesis, and steps toward target identification of the novel 2-amino-3-hydroxyindole anti-malaria drug class. 2009.
Buscar texto completoCoqueiro, Wilma dos Santos. Poéticas do deslocamento: O Bildungsroman de autoria feminina contemporânea. Brazil Publishing, 2021. http://dx.doi.org/10.31012/978-65-5861-338-1.
Texto completoRyoo, Jean J., Jane Margolis y Charis JB. Power On! The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14166.001.0001.
Texto completoCarmean, Karen. Ernest J. Gaines. Greenwood, 1998. http://dx.doi.org/10.5040/9798400647208.
Texto completoCao, Gang y Lance DeLong. Physics of Spin-Orbit-Coupled Oxides. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780199602025.001.0001.
Texto completoZangwill, Andrew. A Mind Over Matter. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198869108.001.0001.
Texto completoZola, Émile. The Ladies' Paradise. Traducido por Brian Nelson. Oxford University Press, 2008. http://dx.doi.org/10.1093/owc/9780199536900.001.0001.
Texto completoCrease, Robert P. y Peter D. Bond. The Leak. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14577.001.0001.
Texto completoEliot, George y K. M. Newton. Daniel Deronda. Editado por Graham Handley. Oxford University Press, 2014. http://dx.doi.org/10.1093/owc/9780199682867.001.0001.
Texto completoCapítulos de libros sobre el tema "Novel class discovery"
Roy, Subhankar, Mingxuan Liu, Zhun Zhong, Nicu Sebe y Elisa Ricci. "Class-Incremental Novel Class Discovery". En Lecture Notes in Computer Science, 317–33. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19827-4_19.
Texto completoJoseph, K. J., Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han y Vineeth N. Balasubramanian. "Novel Class Discovery Without Forgetting". En Lecture Notes in Computer Science, 570–86. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20053-3_33.
Texto completoNguyen, Hung, Xuejian Wang y Leman Akoglu. "Continual Rare-Class Recognition with Emerging Novel Subclasses". En Machine Learning and Knowledge Discovery in Databases, 20–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46147-8_2.
Texto completoFeng, Wei, Lie Ju, Lin Wang, Kaimin Song y Zongyuan Ge. "Towards Novel Class Discovery: A Study in Novel Skin Lesions Clustering". En Lecture Notes in Computer Science, 24–33. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43987-2_3.
Texto completoIslam, Mohammad Raihanul. "Recurring and Novel Class Detection in Concept-Drifting Data Streams Using Class-Based Ensemble". En Advances in Knowledge Discovery and Data Mining, 425–36. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06605-9_35.
Texto completoKefi, Takoua, Riadh Ksantini, Mohamed Bécha Kaâniche y Adel Bouhoula. "A Novel Incremental Covariance-Guided One-Class Support Vector Machine". En Machine Learning and Knowledge Discovery in Databases, 17–32. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46227-1_2.
Texto completoSwalley, Susanne E. y Atwood K. Cheung. "Chapter 8. Identification of a Novel Class of Small Molecules for Spinal Muscular Atrophy Through High-throughput Phenotypic Screening". En Drug Discovery, 140–59. Cambridge: Royal Society of Chemistry, 2020. http://dx.doi.org/10.1039/9781839160721-00140.
Texto completoTroisemaine, Colin, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton y Vincent Lemaire. "An Interactive Interface for Novel Class Discovery in Tabular Data". En Lecture Notes in Computer Science, 295–99. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43430-3_18.
Texto completoHassan, Md Rafiul, Kotagiri Ramamohanarao, Chandan Karmakar, M. Maruf Hossain y James Bailey. "A Novel Scalable Multi-class ROC for Effective Visualization and Computation". En Advances in Knowledge Discovery and Data Mining, 107–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13657-3_14.
Texto completoMasud, Mohammad M., Jing Gao, Latifur Khan, Jiawei Han y Bhavani Thuraisingham. "Classification and Novel Class Detection in Data Streams with Active Mining". En Advances in Knowledge Discovery and Data Mining, 311–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13672-6_31.
Texto completoActas de conferencias sobre el tema "Novel class discovery"
Michalski, Tomasz, Dawid Rymarczyk, Daniel Barczyk y Bartosz Zieliński. "ProtoNCD: Prototypical Parts for Interpretable Novel Class Discovery". En ESANN 2024, 273–78. Louvain-la-Neuve (Belgium): Ciaco - i6doc.com, 2024. http://dx.doi.org/10.14428/esann/2024.es2024-70.
Texto completoLiu, Yu, Yaqi Cai, Qi Jia, Binglin Qiu, Weimin Wang y Nan Pu. "Novel Class Discovery for Ultra-Fine-Grained Visual Categorization". En 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 17679–88. IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.01674.
Texto completoLiu, Jiaming, Yangqiming Wang, Tongze Zhang, Yulu Fan, Qinli Yang y Junming Shao. "Open-world Semi-supervised Novel Class Discovery". En Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/445.
Texto completoGu, Peiyan, Chuyu Zhang, Ruijie Xu y Xuming He. "Class-relation Knowledge Distillation for Novel Class Discovery". En 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2023. http://dx.doi.org/10.1109/iccv51070.2023.01510.
Texto completoZhao, Yuyang, Zhun Zhong, Nicu Sebe y Gim Hee Lee. "Novel Class Discovery in Semantic Segmentation". En 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2022. http://dx.doi.org/10.1109/cvpr52688.2022.00430.
Texto completoMukherjee, Tanmoy y Nikos Deligiannis. "Novel Class Discovery: A Dependency Approach". En ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9747827.
Texto completoLi, Wenbin, Zhichen Fan, Jing Huo y Yang Gao. "Modeling Inter-Class and Intra-Class Constraints in Novel Class Discovery". En 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2023. http://dx.doi.org/10.1109/cvpr52729.2023.00336.
Texto completoZhong, Zhun, Enrico Fini, Subhankar Roy, Zhiming Luo, Elisa Ricci y Nicu Sebe. "Neighborhood Contrastive Learning for Novel Class Discovery". En 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2021. http://dx.doi.org/10.1109/cvpr46437.2021.01072.
Texto completoFini, Enrico, Enver Sangineto, Stephane Lathuiliere, Zhun Zhong, Moin Nabi y Elisa Ricci. "A Unified Objective for Novel Class Discovery". En 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2021. http://dx.doi.org/10.1109/iccv48922.2021.00915.
Texto completoWei, Qian, Zongyong Cui, Yijie Deng, Bin Li y Zongjie Cao. "Research on Novel Class Discovery of SAR Target". En IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2023. http://dx.doi.org/10.1109/igarss52108.2023.10283051.
Texto completoInformes sobre el tema "Novel class discovery"
Barkan, Terrance. The Role of Graphene in Achieving e-Mobility in Aerospace Applications. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, diciembre de 2022. http://dx.doi.org/10.4271/epr2022030.
Texto completoAltstein, Miriam y Ronald J. Nachman. Rational Design of Insect Control Agent Prototypes Based on Pyrokinin/PBAN Neuropeptide Antagonists. United States Department of Agriculture, agosto de 2013. http://dx.doi.org/10.32747/2013.7593398.bard.
Texto completoDawson, William O. y Moshe Bar-Joseph. Creating an Ally from an Adversary: Genetic Manipulation of Citrus Tristeza. United States Department of Agriculture, enero de 2004. http://dx.doi.org/10.32747/2004.7586540.bard.
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