„supervised learning“

Suchergebnisse

2.377 Treffer

• Representation learning via a semi-supervised stacked distance autoencoder for image classification
  Hou, Liang ; Luo, Xiao-yi ; Wang, Zi-yang ; Liang, Jun
• Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization
  Coleman, Brian C. ; Fodeh, Samah ; Lisi, Anthony J. ; Goulet, Joseph L. ; Corcoran, Kelsey L. ; Bathulapalli, Harini ; Brandt, Cynthia A.
• EEMD assisted supervised learning for the fault diagnosis of BLDC motor using vibration signal
  Shifat, Tanvir Alam ; Hur, Jang-Wook
• Predictive Supervised Machine Learning Models for Diabetes Mellitus
  Muhammad, L. J. ; Algehyne, Ebrahem A. ; Usman, Sani Sharif
• Semi-Supervised Subspace Learning for Pattern Classification via Robust Low Rank Constraint
  Li, Ao ; An, Ruoqi ; Chen, Deyun ; Sun, Guanglu ; Liu, Xin ; Wu, Qidi ; Jiang, Hailong
• Weakly supervised learning in neural encoding for the position of the moving finger of a macaque
  Feng, Jingyi ; Wu, Haifeng ; Zeng, Yu ; Wang, Yuhong
• Fast contour detection with supervised attention learning
  Zhang, Rufeng ; You, Mingyu
• DISC: a highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning
  He, Yao ; Yuan, Hao ; Wu, Cheng ; Xie, Zhi
• A data-efficient self-supervised deep learning model for design and characterization of nanophotonic structures
  Ma, Wei ; Liu, Yongmin
• Supervised learning of gene-regulatory networks based on graph distance profiles of transcriptomics data
  Razaghi-Moghadam, Zahra ; Nikoloski, Zoran
• TIME SERIES LAND COVER CLASSIFICATION BASED ON SEMI-SUPERVISED CONVOLUTIONAL LONG SHORT-TERM MEMORY NEURAL NETWORKS
  Jing, S. ; Chao, T.
• GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data
  Rue-Albrecht, Kévin ; McGettigan, Paul A. ; Hernández, Belinda ; Nalpas, Nicolas C. ; Magee, David A. ; Parnell, Andrew C. ; Gordon, Stephen V. ; MacHugh, David E.
• Strategies for Learning Groundwater Potential Modelling Indices under Sparse Data with Supervised and Unsupervised Techniques
  Karimi, V. ; Khatibi, R. ; Ghorbani, M. A. ; Bui, D. Tien ; Darbandi, S.
• MaskMitosis: a deep learning framework for fully supervised, weakly supervised, and unsupervised mitosis detection in histopathology images
  Sebai, Meriem ; Wang, Xinggang ; Wang, Tianjiang
• Statistisches und maschinelles Lernen – gängige Verfahren im Überblick
  Richter, Stefan 2019 Springer Spektrum
• Extreme Learning Machine for Supervised Classification with Self-paced Learning
  Li, Li ; Zhao, Kaiyi ; Li, Sicong ; Sun, Ruizhi ; Cai, Saihua
• Supervised machine learning approach to predict qualitative software product
  Sinha, Hariom ; Behera, Rajat Kumar
• Transactions on edutainment
  Pan, Zhigeng ; Cheok, Adrian David ; Müller, Wolfgang 2011 Springer
• WEAKLY SUPERVISED SEMANTIC SEGMENTATION OF SATELLITE IMAGES FOR LAND COVER MAPPING – CHALLENGES AND OPPORTUNITIES
  Schmitt, M. ; Prexl, J. ; Ebel, P. ; Liebel, L. ; Zhu, X. X.
• COMPONENT SUBSTITUTION NETWORK FOR PAN-SHARPENING VIA SEMI-SUPERVISED LEARNING
  Liu, C. ; Zhang, Y. ; Ou, Y.