Статті в журналах з теми "T-stochastic neighbor embedding"
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Chan, David M., Roshan Rao, Forrest Huang, and John F. Canny. "GPU accelerated t-distributed stochastic neighbor embedding." Journal of Parallel and Distributed Computing 131 (September 2019): 1–13. http://dx.doi.org/10.1016/j.jpdc.2019.04.008.
Повний текст джерелаHuang, Yanyong, Kejun Guo, Xiuwen Yi, Jing Yu, Zongxin Shen, and Tianrui Li. "T-copula and Wasserstein distance-based stochastic neighbor embedding." Knowledge-Based Systems 243 (May 2022): 108431. http://dx.doi.org/10.1016/j.knosys.2022.108431.
Повний текст джерелаValente, Daria, Chiara De Gregorio, Valeria Torti, Longondraza Miaretsoa, Olivier Friard, Rose Marie Randrianarison, Cristina Giacoma, and Marco Gamba. "Finding Meanings in Low Dimensional Structures: Stochastic Neighbor Embedding Applied to the Analysis of Indri indri Vocal Repertoire." Animals 9, no. 5 (May 15, 2019): 243. http://dx.doi.org/10.3390/ani9050243.
Повний текст джерелаYu, Meiting, Lingjun Zhao, Siqian Zhang, Boli Xiong, and Gangyao Kuang. "SAR target recognition using parametric supervised t-stochastic neighbor embedding." Remote Sensing Letters 8, no. 9 (May 28, 2017): 849–58. http://dx.doi.org/10.1080/2150704x.2017.1332795.
Повний текст джерелаZhang, Haili, Pu Wang, Xuejin Gao, Yongsheng Qi, and Huihui Gao. "Process Data Visualization Using Bikernel t-Distributed Stochastic Neighbor Embedding." Industrial & Engineering Chemistry Research 59, no. 44 (October 21, 2020): 19623–32. http://dx.doi.org/10.1021/acs.iecr.0c03333.
Повний текст джерелаZhang, Qiang, Yi Yao, Dongsheng Zhou, and Rui Liu. "Motion Key-Frame Extraction by Using Optimized t-Stochastic Neighbor Embedding." Symmetry 7, no. 2 (April 21, 2015): 395–411. http://dx.doi.org/10.3390/sym7020395.
Повний текст джерелаPitsianis, Nikos, Dimitris Floros, Alexandros-Stavros Iliopoulos та Xiaobai Sun. "SG-t-SNE-Π: Swift Neighbor Embedding of Sparse Stochastic Graphs". Journal of Open Source Software 4, № 39 (31 липня 2019): 1577. http://dx.doi.org/10.21105/joss.01577.
Повний текст джерелаCieslak, Matthew C., Ann M. Castelfranco, Vittoria Roncalli, Petra H. Lenz, and Daniel K. Hartline. "t-Distributed Stochastic Neighbor Embedding (t-SNE): A tool for eco-physiological transcriptomic analysis." Marine Genomics 51 (June 2020): 100723. http://dx.doi.org/10.1016/j.margen.2019.100723.
Повний текст джерелаMa, Xiaobo, Yuchen Zhang, Fengshan Zhang, and Hongbin Liu. "Monitoring of papermaking wastewater treatment processes using t-distributed stochastic neighbor embedding." Journal of Environmental Chemical Engineering 9, no. 6 (December 2021): 106559. http://dx.doi.org/10.1016/j.jece.2021.106559.
Повний текст джерелаKoolstra, Kirsten, Peter Börnert, Boudewijn P. F. Lelieveldt, Andrew Webb, and Oleh Dzyubachyk. "Stochastic neighbor embedding as a tool for visualizing the encoding capability of magnetic resonance fingerprinting dictionaries." Magnetic Resonance Materials in Physics, Biology and Medicine 35, no. 2 (October 23, 2021): 223–34. http://dx.doi.org/10.1007/s10334-021-00963-8.
Повний текст джерелаLu, Weipeng, and Xuefeng Yan. "Industrial process data visualization based on a deep enhanced t-distributed stochastic neighbor embedding neural network." Assembly Automation 42, no. 2 (March 18, 2022): 268–77. http://dx.doi.org/10.1108/aa-09-2021-0123.
Повний текст джерелаVerma, Meetu, Gal Matijevič, Carsten Denker, Andrea Diercke, Ekaterina Dineva, Horst Balthasar, Robert Kamlah, Ioannis Kontogiannis, Christoph Kuckein та Partha S. Pal. "Classification of High-resolution Solar Hα Spectra Using t-distributed Stochastic Neighbor Embedding". Astrophysical Journal 907, № 1 (28 січня 2021): 54. http://dx.doi.org/10.3847/1538-4357/abcd95.
Повний текст джерелаHu, Ying, Xiaobing Li, Lijia Wang, Baosan Han, and Shengdong Nie. "T-distribution stochastic neighbor embedding for fine brain functional parcellation on rs-fMRI." Brain Research Bulletin 162 (September 2020): 199–207. http://dx.doi.org/10.1016/j.brainresbull.2020.06.007.
Повний текст джерелаWang, Zhi‐Lei, Toshio Ogawa, and Yoshitaka Adachi. "Persistent‐Homology‐Based Microstructural Optimization of Materials Using t‐Distributed Stochastic Neighbor Embedding." Advanced Theory and Simulations 3, no. 7 (June 5, 2020): 2000040. http://dx.doi.org/10.1002/adts.202000040.
Повний текст джерелаLeon-Medina, Jersson X., Maribel Anaya, Francesc Pozo, and Diego Tibaduiza. "Nonlinear Feature Extraction Through Manifold Learning in an Electronic Tongue Classification Task." Sensors 20, no. 17 (August 27, 2020): 4834. http://dx.doi.org/10.3390/s20174834.
Повний текст джерелаGajjar, Pranshav, Naishadh Mehta, and Pooja Shah. "Quadruplet loss and SqueezeNets for Covid-19 detection from Chest-X ray." Computer Science Journal of Moldova 30, no. 2 (89) (July 2022): 214–22. http://dx.doi.org/10.56415/csjm.v30.12.
Повний текст джерелаGao, Lianru, Daixin Gu, Lina Zhuang, Jinchang Ren, Dong Yang, and Bing Zhang. "Combining t-Distributed Stochastic Neighbor Embedding With Convolutional Neural Networks for Hyperspectral Image Classification." IEEE Geoscience and Remote Sensing Letters 17, no. 8 (August 2020): 1368–72. http://dx.doi.org/10.1109/lgrs.2019.2945122.
Повний текст джерелаZhou, Hongyu, Feng Wang, and Peng Tao. "t-Distributed Stochastic Neighbor Embedding Method with the Least Information Loss for Macromolecular Simulations." Journal of Chemical Theory and Computation 14, no. 11 (September 25, 2018): 5499–510. http://dx.doi.org/10.1021/acs.jctc.8b00652.
Повний текст джерелаZhu, Wenbo, Zachary T. Webb, Kaitian Mao, and José Romagnoli. "A Deep Learning Approach for Process Data Visualization Using t-Distributed Stochastic Neighbor Embedding." Industrial & Engineering Chemistry Research 58, no. 22 (May 16, 2019): 9564–75. http://dx.doi.org/10.1021/acs.iecr.9b00975.
Повний текст джерелаTadjer, Amine, Reider B. Bratvold, and Remus G. Hanea. "Efficient Dimensionality Reduction Methods in Reservoir History Matching." Energies 14, no. 11 (May 27, 2021): 3137. http://dx.doi.org/10.3390/en14113137.
Повний текст джерелаFang, Xian, Zhixin Tie, Yinan Guan, and Shanshan Rao. "Quasi-cluster centers clustering algorithm based on potential entropy and t-distributed stochastic neighbor embedding." Soft Computing 23, no. 14 (May 11, 2018): 5645–57. http://dx.doi.org/10.1007/s00500-018-3221-y.
Повний текст джерелаTu, Deyu, Jinde Zheng, Zhanwei Jiang, and Haiyang Pan. "Multiscale Distribution Entropy and t-Distributed Stochastic Neighbor Embedding-Based Fault Diagnosis of Rolling Bearings." Entropy 20, no. 5 (May 11, 2018): 360. http://dx.doi.org/10.3390/e20050360.
Повний текст джерелаAcuff, Nicole V., and Joel Linden. "Using Visualization of t-Distributed Stochastic Neighbor Embedding To Identify Immune Cell Subsets in Mouse Tumors." Journal of Immunology 198, no. 11 (May 3, 2017): 4539–46. http://dx.doi.org/10.4049/jimmunol.1602077.
Повний текст джерелаDemidova, Liliya A., and Artyom V. Gorchakov. "Fuzzy Information Discrimination Measures and Their Application to Low Dimensional Embedding Construction in the UMAP Algorithm." Journal of Imaging 8, no. 4 (April 15, 2022): 113. http://dx.doi.org/10.3390/jimaging8040113.
Повний текст джерелаLiu, Honghua, Jing Yang, Ming Ye, Scott C. James, Zhonghua Tang, Jie Dong, and Tongju Xing. "Using t-distributed Stochastic Neighbor Embedding (t-SNE) for cluster analysis and spatial zone delineation of groundwater geochemistry data." Journal of Hydrology 597 (June 2021): 126146. http://dx.doi.org/10.1016/j.jhydrol.2021.126146.
Повний текст джерелаTao, Shiyong, Weirong Chen, Shuna Jiang, Xinyu Liu, and Jiaxi Yu. "INTELLIGENT HEALTH STATUS DETECTION METHOD FOR LOCOMOTIVE FUEL CELL BASED ON DATA-DRIVEN TECHNIQUES." DYNA 96, no. 6 (November 1, 2021): 633–39. http://dx.doi.org/10.6036/10290.
Повний текст джерелаGu, Haoyu, and Li Wang. "Modified t-Distribution Stochastic Neighbor Embedding Using Augmented Kernel Mahalanobis-Distance for Dynamic Multimode Chemical Process Monitoring." International Journal of Chemical Engineering 2022 (December 29, 2022): 1–19. http://dx.doi.org/10.1155/2022/8460463.
Повний текст джерелаPouyet, Emeline, Neda Rohani, Aggelos K. Katsaggelos, Oliver Cossairt, and Marc Walton. "Innovative data reduction and visualization strategy for hyperspectral imaging datasets using t-SNE approach." Pure and Applied Chemistry 90, no. 3 (February 23, 2018): 493–506. http://dx.doi.org/10.1515/pac-2017-0907.
Повний текст джерелаLeon-Medina, Jersson X., Maribel Anaya, and Diego Alexander Tibaduiza. "T-Distributed Stochastic Neighbor Embedding to Improve the Discrimination of Yogurt Using a Multistep Amperometry Electronic Tongue." ECS Meeting Abstracts MA2021-01, no. 64 (May 30, 2021): 2061. http://dx.doi.org/10.1149/ma2021-01642061mtgabs.
Повний текст джерелаZarzar, Mouayad, Eliza Razak, Zaw Zaw Htike, and Faridah Yusof. "Early Diagnosis of Non-Small-Cell Lung Carcinoma from Gene Expression Using t-Distributed Stochastic Neighbor Embedding." Advanced Science Letters 21, no. 11 (November 1, 2015): 3550–53. http://dx.doi.org/10.1166/asl.2015.6587.
Повний текст джерелаWu, Hao, Dahai Dai, and Xuesong Wang. "A Novel Radar HRRP Recognition Method with Accelerated T-Distributed Stochastic Neighbor Embedding and Density-Based Clustering." Sensors 19, no. 23 (November 22, 2019): 5112. http://dx.doi.org/10.3390/s19235112.
Повний текст джерелаLi, Wentian, Jane E. Cerise, Yaning Yang, and Henry Han. "Application of t-SNE to human genetic data." Journal of Bioinformatics and Computational Biology 15, no. 04 (August 2017): 1750017. http://dx.doi.org/10.1142/s0219720017500172.
Повний текст джерелаAbdelmoula, Walid M., Benjamin Balluff, Sonja Englert, Jouke Dijkstra, Marcel J. T. Reinders, Axel Walch, Liam A. McDonnell, and Boudewijn P. F. Lelieveldt. "Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data." Proceedings of the National Academy of Sciences 113, no. 43 (October 10, 2016): 12244–49. http://dx.doi.org/10.1073/pnas.1510227113.
Повний текст джерелаHäkkinen, Antti, Juha Koiranen, Julia Casado, Katja Kaipio, Oskari Lehtonen, Eleonora Petrucci, Johanna Hynninen, et al. "qSNE: quadratic rate t-SNE optimizer with automatic parameter tuning for large datasets." Bioinformatics 36, no. 20 (July 14, 2020): 5086–92. http://dx.doi.org/10.1093/bioinformatics/btaa637.
Повний текст джерелаSchmitz, S., U. Weidner, H. Hammer, and A. Thiele. "EVALUATING UNIFORM MANIFOLD APPROXIMATION AND PROJECTION FOR DIMENSION REDUCTION AND VISUALIZATION OF POLINSAR FEATURES." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2021 (June 17, 2021): 39–46. http://dx.doi.org/10.5194/isprs-annals-v-1-2021-39-2021.
Повний текст джерелаWalsh, Joe, Ian Timothy Heazlewood, Mark DeBeliso, and Mike Climstein. "Application of t-distributed Stochastic Neighbor Embedding (t-SNE) to clustering of social affiliation and recognition psychological motivations in masters athletes." International Journal of Sport, Exercise and Health Research 4, no. 1 (May 31, 2020): 1–6. http://dx.doi.org/10.31254/sportmed.4101.
Повний текст джерелаMeyer, Bruno Henrique, Aurora Trinidad Ramirez Pozo, and Wagner M. Nunan Zola. "Improving Barnes-Hut t-SNE Algorithm in Modern GPU Architectures with Random Forest KNN and Simulated Wide-Warp." ACM Journal on Emerging Technologies in Computing Systems 17, no. 4 (June 30, 2021): 1–26. http://dx.doi.org/10.1145/3447779.
Повний текст джерелаSchwarz, Christian, Rebecca Buchholz, Muhammad Jawad, Vanessa Hoesker, Claudia Terwesten-Solé, Uwe Karst, Lars Linsen, et al. "Fingerprints of Element Concentrations in Infective Endocarditis Obtained by Mass Spectrometric Imaging and t-Distributed Stochastic Neighbor Embedding." ACS Infectious Diseases 8, no. 2 (January 19, 2022): 360–72. http://dx.doi.org/10.1021/acsinfecdis.1c00485.
Повний текст джерелаTao, Keyu, Jian Cao, Yuce Wang, Julei Mi, Wanyun Ma, and Chunhua Shi. "Chemometric Classification of Crude Oils in Complex Petroleum Systems Using t-Distributed Stochastic Neighbor Embedding Machine Learning Algorithm." Energy & Fuels 34, no. 5 (April 28, 2020): 5884–99. http://dx.doi.org/10.1021/acs.energyfuels.0c01333.
Повний текст джерелаHorn, Nils, Fabian Gampfer, and Rüdiger Buchkremer. "Latent Dirichlet Allocation and t-Distributed Stochastic Neighbor Embedding Enhance Scientific Reading Comprehension of Articles Related to Enterprise Architecture." AI 2, no. 2 (April 22, 2021): 179–94. http://dx.doi.org/10.3390/ai2020011.
Повний текст джерелаOliveira, Fábio Henrique M., Alessandro R. P. Machado, and Adriano O. Andrade. "On the Use of t-Distributed Stochastic Neighbor Embedding for Data Visualization and Classification of Individuals with Parkinson’s Disease." Computational and Mathematical Methods in Medicine 2018 (November 4, 2018): 1–17. http://dx.doi.org/10.1155/2018/8019232.
Повний текст джерелаSenigagliesi, Linda, Gianluca Ciattaglia, Adelmo De Santis, and Ennio Gambi. "People Walking Classification Using Automotive Radar." Electronics 9, no. 4 (March 30, 2020): 588. http://dx.doi.org/10.3390/electronics9040588.
Повний текст джерелаBezrukov, N. S., and E. V. Polyanskaya. "CONSTRUCTION OF A DATA CLUSTERING MODEL EXEMPLIFIED BY DEMO-GRAPHIC INDICATORS OF THE FEFD REGIONS." Informatika i sistemy upravleniya, no. 4 (2021): 3–12. http://dx.doi.org/10.22250/isu.2021.70.3-12.
Повний текст джерелаHan, Yongming, Shuang Liu, Di Cong, Zhiqiang Geng, Jinzhen Fan, Jingyang Gao, and Tingrui Pan. "Resource optimization model using novel extreme learning machine with t-distributed stochastic neighbor embedding: Application to complex industrial processes." Energy 225 (June 2021): 120255. http://dx.doi.org/10.1016/j.energy.2021.120255.
Повний текст джерелаEt al., Hariharan S. "Analysing Effect of t-SNE and 1-D CNN on Performance of Hyperspectral Image Classification." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 5, 2021): 1828–33. http://dx.doi.org/10.17762/turcomat.v12i6.4166.
Повний текст джерелаWang, Yuliang, Huiyi Su, and Mingshi Li. "An Improved Model Based Detection of Urban Impervious Surfaces Using Multiple Features Extracted from ROSIS-3 Hyperspectral Images." Remote Sensing 11, no. 2 (January 11, 2019): 136. http://dx.doi.org/10.3390/rs11020136.
Повний текст джерелаLiu, Xiaoyuan, Senxiang Lu, Yan Ren, and Zhenning Wu. "Wind Turbine Anomaly Detection Based on SCADA Data Mining." Electronics 9, no. 5 (May 2, 2020): 751. http://dx.doi.org/10.3390/electronics9050751.
Повний текст джерелаKiran, Mariam, Scott Campbell, Fatema Bannat Wala, Nick Buraglio, and Inder Monga. "Machine learning-based analysis of COVID-19 pandemic impact on US research networks." ACM SIGCOMM Computer Communication Review 51, no. 4 (October 24, 2021): 23–35. http://dx.doi.org/10.1145/3503954.3503958.
Повний текст джерелаSonnewald, Maike, Stephanie Dutkiewicz, Christopher Hill, and Gael Forget. "Elucidating ecological complexity: Unsupervised learning determines global marine eco-provinces." Science Advances 6, no. 22 (May 2020): eaay4740. http://dx.doi.org/10.1126/sciadv.aay4740.
Повний текст джерелаLiu, Xiaobo, Hantao Guo, and Yibing Liu. "One-Shot Fault Diagnosis of Wind Turbines Based on Meta-Analogical Momentum Contrast Learning." Energies 15, no. 9 (April 25, 2022): 3133. http://dx.doi.org/10.3390/en15093133.
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