Literatura académica sobre el tema "Limited training data"
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Artículos de revistas sobre el tema "Limited training data"
Oh, Se Eun, Nate Mathews, Mohammad Saidur Rahman, Matthew Wright y Nicholas Hopper. "GANDaLF: GAN for Data-Limited Fingerprinting". Proceedings on Privacy Enhancing Technologies 2021, n.º 2 (29 de enero de 2021): 305–22. http://dx.doi.org/10.2478/popets-2021-0029.
Texto completoMcLaughlin, Niall, Ji Ming y Danny Crookes. "Robust Multimodal Person Identification With Limited Training Data". IEEE Transactions on Human-Machine Systems 43, n.º 2 (marzo de 2013): 214–24. http://dx.doi.org/10.1109/tsmcc.2012.2227959.
Texto completoZhang, Mingyang, Berrak Sisman, Li Zhao y Haizhou Li. "DeepConversion: Voice conversion with limited parallel training data". Speech Communication 122 (septiembre de 2020): 31–43. http://dx.doi.org/10.1016/j.specom.2020.05.004.
Texto completoQian, Tieyun, Bing Liu, Li Chen, Zhiyong Peng, Ming Zhong, Guoliang He, Xuhui Li y Gang Xu. "Tri-Training for authorship attribution with limited training data: a comprehensive study". Neurocomputing 171 (enero de 2016): 798–806. http://dx.doi.org/10.1016/j.neucom.2015.07.064.
Texto completoSaunders, Sara L., Ethan Leng, Benjamin Spilseth, Neil Wasserman, Gregory J. Metzger y Patrick J. Bolan. "Training Convolutional Networks for Prostate Segmentation With Limited Data". IEEE Access 9 (2021): 109214–23. http://dx.doi.org/10.1109/access.2021.3100585.
Texto completoZhao, Yao, Dong Joo Rhee, Carlos Cardenas, Laurence E. Court y Jinzhong Yang. "Training deep‐learning segmentation models from severely limited data". Medical Physics 48, n.º 4 (19 de febrero de 2021): 1697–706. http://dx.doi.org/10.1002/mp.14728.
Texto completoHoffbeck, J. P. y D. A. Landgrebe. "Covariance matrix estimation and classification with limited training data". IEEE Transactions on Pattern Analysis and Machine Intelligence 18, n.º 7 (julio de 1996): 763–67. http://dx.doi.org/10.1109/34.506799.
Texto completoCui, Kaiwen, Jiaxing Huang, Zhipeng Luo, Gongjie Zhang, Fangneng Zhan y Shijian Lu. "GenCo: Generative Co-training for Generative Adversarial Networks with Limited Data". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 1 (28 de junio de 2022): 499–507. http://dx.doi.org/10.1609/aaai.v36i1.19928.
Texto completoKim, June-Woo y Ho-Young Jung. "End-to-end speech recognition models using limited training data*". Phonetics and Speech Sciences 12, n.º 4 (diciembre de 2020): 63–71. http://dx.doi.org/10.13064/ksss.2020.12.4.063.
Texto completoTambouratzis, George y Marina Vassiliou. "Swarm Algorithms for NLP - The Case of Limited Training Data". Journal of Artificial Intelligence and Soft Computing Research 9, n.º 3 (1 de julio de 2019): 219–34. http://dx.doi.org/10.2478/jaiscr-2019-0005.
Texto completoTesis sobre el tema "Limited training data"
Chang, Eric I.-Chao. "Improving wordspotting performance with limited training data". Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/38056.
Texto completoIncludes bibliographical references (leaves 149-155).
by Eric I-Chao Chang.
Ph.D.
Zama, Ramirez Pierluigi <1992>. "Deep Scene Understanding with Limited Training Data". Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amsdottorato.unibo.it/9815/1/zamaramirez_pierluigi_tesi.pdf.
Texto completoMcLaughlin, N. R. "Robust multimodal person identification given limited training data". Thesis, Queen's University Belfast, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.579747.
Texto completoLi, Jiawei. "Person re-identification with limited labeled training data". HKBU Institutional Repository, 2018. https://repository.hkbu.edu.hk/etd_oa/541.
Texto completoQu, Lizhen [Verfasser] y Gerhard [Akademischer Betreuer] Weikum. "Sentiment analysis with limited training data / Lizhen Qu. Betreuer: Gerhard Weikum". Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2013. http://d-nb.info/1053680104/34.
Texto completoGuo, Zhenyu. "Data famine in big data era : machine learning algorithms for visual object recognition with limited training data". Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/46412.
Texto completoSäfdal, Joakim. "Data-Driven Engine Fault Classification and Severity Estimation Using Interpolated Fault Modes from Limited Training Data". Thesis, Linköpings universitet, Fordonssystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-173916.
Texto completoLapin, Maksim [Verfasser] y Bernt [Akademischer Betreuer] Schiele. "Image classification with limited training data and class ambiguity / Maksim Lapin ; Betreuer: Bernt Schiele". Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2017. http://d-nb.info/1136607927/34.
Texto completoTrávníčková, Kateřina. "Interaktivní segmentace 3D CT dat s využitím hlubokého učení". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-432864.
Texto completoMorgan, Joseph Troy. "Adaptive hierarchical classification with limited training data". Thesis, 2002. http://wwwlib.umi.com/cr/utexas/fullcit?p3115506.
Texto completoLibros sobre el tema "Limited training data"
Adaptive Hierarchial Classification with Limited Training Data. Storming Media, 2002.
Buscar texto completoMalina, Robert M. The influence of physical activity and training on growth and maturation. Editado por Neil Armstrong y Willem van Mechelen. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198757672.003.0032.
Texto completoRaveesh, B. N., Swaran P. Singh y Soumitra Pathare. Coercion and mental health services in the Indian subcontinent and the Middle East. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198788065.003.0016.
Texto completoFinancial management: Control weaknesses limited Customs' ability to ensure that duties were properly assessed : report to the Commissioner, U.S. Customs Service. Washington, D.C: The Office, 1994.
Buscar texto completoDallmeijer, Annet y Jost Schnyder. Exercise capacity and training in cerebral palsy and other neuromuscular diseases. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199232482.003.0035.
Texto completoWilliams, Craig A. Maximal intensity exercise. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199232482.003.0017.
Texto completoWolbarst, Anthony y Nathan Yanasak. An Introduction to MRI. Medical Physics Publishing, 2019. http://dx.doi.org/10.54947/9781930524200.
Texto completoCapítulos de libros sobre el tema "Limited training data"
Thuraisingham, Bhavani, Mohammad Mehedy Masud, Pallabi Parveen y Latifur Khan. "Data Stream Classification with Limited Labeled Training Data". En Big Data Analytics with Applications in Insider Threat Detection, 149–70. Boca Raton : Taylor & Francis, CRC Press, 2017.: Auerbach Publications, 2017. http://dx.doi.org/10.1201/9781315119458-14.
Texto completoSong, Jingkuan, Xu Zhao, Lianli Gao y Liangliang Cao. "Large-Scale Video Understanding with Limited Training Labels". En Big Data Analytics for Large-Scale Multimedia Search, 89–120. Chichester, UK: John Wiley & Sons, Ltd, 2019. http://dx.doi.org/10.1002/9781119376996.ch4.
Texto completoZhang, Bodong, Beatrice Knudsen, Deepika Sirohi, Alessandro Ferrero y Tolga Tasdizen. "Stain Based Contrastive Co-training for Histopathological Image Analysis". En Medical Image Learning with Limited and Noisy Data, 106–16. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16760-7_11.
Texto completoZhang, Yiqing, Yimeng Dai, Jianzhong Qi, Xinxing Xu y Rui Zhang. "Citation Field Learning by RNN with Limited Training Data". En Lecture Notes in Computer Science, 219–32. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04503-6_23.
Texto completoTseng, Shih-Lun y Huei-Yung Lin. "Fish Detection Using Convolutional Neural Networks with Limited Training Data". En Lecture Notes in Computer Science, 735–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41404-7_52.
Texto completoDing, Guoli, Jianhua Chen, Robert Lax y Peter Chen. "Efficient Learning of Pseudo-Boolean Functions from Limited Training Data". En Lecture Notes in Computer Science, 323–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11425274_34.
Texto completoNaga, Varun, Tejas Sudharshan Mathai, Angshuman Paul y Ronald M. Summers. "Universal Lesion Detection and Classification Using Limited Data and Weakly-Supervised Self-training". En Medical Image Learning with Limited and Noisy Data, 55–64. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16760-7_6.
Texto completoHu, Yangwen, Zhehao Zhong, Ruixuan Wang, Hongmei Liu, Zhijun Tan y Wei-Shi Zheng. "Data Augmentation in Logit Space for Medical Image Classification with Limited Training Data". En Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 469–79. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87240-3_45.
Texto completoPace, Danielle F., Adrian V. Dalca, Tom Brosch, Tal Geva, Andrew J. Powell, Jürgen Weese, Mehdi H. Moghari y Polina Golland. "Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease". En Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 334–42. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00889-5_38.
Texto completoGalke, Lukas, Gunnar Gerstenkorn y Ansgar Scherp. "A Case Study of Closed-Domain Response Suggestion with Limited Training Data". En Communications in Computer and Information Science, 218–29. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99133-7_18.
Texto completoActas de conferencias sobre el tema "Limited training data"
Milan, A., T. Pham, K. Vijay, D. Morrison, A. W. Tow, L. Liu, J. Erskine et al. "Semantic Segmentation from Limited Training Data". En 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. http://dx.doi.org/10.1109/icra.2018.8461082.
Texto completoWang, S. L., W. H. Lau y S. H. Leung. "Automatic Lipreading with Limited Training Data". En 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.301.
Texto completoQian, Tieyun, Bing Liu, Li Chen y Zhiyong Peng. "Tri-Training for Authorship Attribution with Limited Training Data". En Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/p14-2057.
Texto completoNguyen, Le T., Ming Zeng, Patrick Tague y Joy Zhang. "Recognizing new activities with limited training data". En the 2015 ACM International Symposium. New York, New York, USA: ACM Press, 2015. http://dx.doi.org/10.1145/2802083.2808388.
Texto completoVaessen, Nik y David van Leeuwen. "Training speaker recognition systems with limited data". En Interspeech 2022. ISCA: ISCA, 2022. http://dx.doi.org/10.21437/interspeech.2022-135.
Texto completoBaertlein, Brian A. y Ajith H. Gunatilaka. "Optimizing fusion architectures for limited training data sets". En AeroSense 2000, editado por Abinash C. Dubey, James F. Harvey, J. Thomas Broach y Regina E. Dugan. SPIE, 2000. http://dx.doi.org/10.1117/12.396308.
Texto completoPeche, Marius, Marelie Davel y Etienne Barnard. "Phonotactic spoken language identification with limited training data". En Interspeech 2007. ISCA: ISCA, 2007. http://dx.doi.org/10.21437/interspeech.2007-443.
Texto completoD'Cruz, Ashwin, Christopher Tegho, Sean Greaves y Lachlan Kermode. "Detecting Tear Gas Canisters With Limited Training Data". En 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2022. http://dx.doi.org/10.1109/wacv51458.2022.00135.
Texto completoWang, Chenwei, Siyi Luo, Lin Liu, Yin Zhang, Jifang Pei, Yulin Huang y Jianyu Yang. "SAR ATR under Limited Training Data Via MobileNetV3". En 2023 IEEE Radar Conference (RadarConf23). IEEE, 2023. http://dx.doi.org/10.1109/radarconf2351548.2023.10149606.
Texto completoLin, James, Kevin Kilgour, Dominik Roblek y Matthew Sharifi. "Training Keyword Spotters with Limited and Synthesized Speech Data". En ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9053193.
Texto completoInformes sobre el tema "Limited training data"
Willi, Joseph, Keith Stakes, Jack Regan y Robin Zevotek. Evaluation of Ventilation-Controlled Fires in L-Shaped Training Props. UL's Firefighter Safety Research Institute, octubre de 2016. http://dx.doi.org/10.54206/102376/mijj9867.
Texto completoPham, Melissa V., William R. Fields, Dustin T. Brown, Dylan A. Pasley, Juan L. Davila-Parez, William D. Meyer y Matthew D. Hiett. Bridge Resource Inventory Database for Gap Emplacement Selection (BRIDGES). U.S. Army Engineer Research and Development Center, julio de 2023. http://dx.doi.org/10.21079/11681/47359.
Texto completoCheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li y Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Texto completoCheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li y Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Texto completoBerney, Ernest, Naveen Ganesh, Andrew Ward, J. Newman y John Rushing. Methodology for remote assessment of pavement distresses from point cloud analysis. Engineer Research and Development Center (U.S.), abril de 2021. http://dx.doi.org/10.21079/11681/40401.
Texto completoKomba, Aneth y Richard Shukia. An Analysis of the Basic Education Curriculum in Tanzania: The Integration, Scope, and Sequence of 21st Century Skills. Research on Improving Systems of Education (RISE), febrero de 2023. http://dx.doi.org/10.35489/bsg-rise-wp_2023/129.
Texto completoBackstrom, Robert y David Dini. Firefighter Safety and Photovoltaic Systems Summary. UL Firefighter Safety Research Institute, noviembre de 2011. http://dx.doi.org/10.54206/102376/kylj9621.
Texto completoBackstrom, Robert y David Backstrom. Firefighter Safety and Photovoltaic Installations Research Project. UL Firefighter Safety Research Institute, noviembre de 2011. http://dx.doi.org/10.54206/102376/viyv4379.
Texto completoTarko, Andrew P., Mario A. Romero, Vamsi Krishna Bandaru y Cristhian Lizarazo. TScan–Stationary LiDAR for Traffic and Safety Applications: Vehicle Interpretation and Tracking. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317402.
Texto completoMegersa, Kelbesa. Effectiveness and Value for Money of Technical Assistance Approaches: In-house vs Contracting. Institute of Development Studies, julio de 2022. http://dx.doi.org/10.19088/k4d.2022.135.
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