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1 |
Establishment and Application of Steel Composition Prediction Model Based on t-Distributed Stochastic Neighbor Embedding (t-SNE) Dimensionality Reduction Algorithm
Enthalten in Journal of sustainable metallurgy 19.3.2024: 1-16
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2 |
Misalignment Detection of Rotating Machine Shaft Using Artificial Neural Network and t-Distributed Stochastic Neighbor Embedding Classification Technique
Enthalten in Journal of control, automation and electrical systems 12.12.2022: 1-8
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3 |
Revealing Geochemical Patterns Associated with Mineralization Using t-Distributed Stochastic Neighbor Embedding and Random Forest
Enthalten in Mathematical geosciences 5.10.2022: 1-24
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4 |
Breast cancer classification using snapshot ensemble deep learning model and t-distributed stochastic neighbor embedding
Enthalten in Multimedia tools and applications 21.7.2022: 1-19
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5 |
Classification of Weld Seam Width Based on Detrended Fluctuation Analysis, t-Distributed Stochastic Neighbor Embedding, and Support Vector Machine
Enthalten in Journal of materials engineering and performance 23.1.2022: 1-10
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6 |
Stochastic neighbor embedding as a tool for visualizing the encoding capability of magnetic resonance fingerprinting dictionaries
Enthalten in Magnetic resonance materials in physics, biology and medicine 23.10.2021: 1-12
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7 |
Persistent‐Homology‐Based Microstructural Optimization of Materials Using t‐Distributed Stochastic Neighbor Embedding
Enthalten in Advanced theory and simulations Bd. 3, 2020, Nr. 7. 4 S.
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8 |
Quasi-cluster centers clustering algorithm based on potential entropy and t-distributed stochastic neighbor embedding
Enthalten in Soft computing 11.5.2018: 1-13
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9 |
A MODIFIED STOCHASTIC NEIGHBOR EMBEDDING FOR COMBINING MULTIPLE FEATURES FOR REMOTE SENSING IMAGE CLASSIFICATION
Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. I-3, 2012: 395-398
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10 |
Fault diagnosis of industrial process based on the optimal parametric t-distributed stochastic neighbor embedding
Enthalten in Science China / Information sciences Bd. 64, 15.6.2020, Nr. 5, date:5.2021: 1-3
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