DUYỆT THEO

HỒ SƠ TÁC GIẢ

Tìm kiếm theo: Chủ đề Machine Learning

Duyệt theo: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
Hoặc nhập chữ cái đầu tiên:  
Kết quả tìm kiếm từ 3 đến 5 trong 5 kết quả
  • BB

  • Semantic segmentation of settlement patterns in gray-scale map images using RF and CRF within an HPC environment

    • Tác giả: Schemala, D. de;  Người hướng dẫn: -;  Người tham gia: - (2016)

  • The segmentation of complex and compound geographical objects such as settlement areas in images is a challenging task. This is particularly true if the images are scanned historical maps, which are only available as gray-scale images. On the other hand, their vast availability and spatio-temporal coverage make these maps a valuable source of information for historical land use and land cover (LULC) research and urban geography. To facilitate the laborious information extraction from these maps, we present a twostage machine learning-based approach for segmenting settlement and non-settlement areas in the map scans. We employ a Conditional Random Field (CRF) which obtains its unary po...
  • BB

  • SSDStreamer: Specializing I/O Stack for Large-Scale Machine Learning

    • Tác giả: Bae, J.;  Người hướng dẫn: -;  Người tham gia: Jang, H.; Gong, J.; Jin, W.; Kim, S.; Jang, J.; Ham, T. J.; Jeong, J.; Lee, J. W. (2019)

  • Abstract—This article presents SSDStreamer, an SSD-based caching system for largescale machine learning. By using DRAM as stream buffer, instead of an upper-level cache, SSDStreamer significantly outperforms state-of-the-art multilevel caching systems on Apache Spark, while requiring much less DRAM capacity.
  • BB

  • Value of feature reduction for crop differentiation using multi-temporal imagery, machine learning, and object-based image analysis.

    • Tác giả: Gilbertson, J.K.;  Người hướng dẫn: -;  Người tham gia: - (2016)

  • This study examined the value of automated and manual feature selection, when applied to machine learning and object-based image analysis (OBIA), for the differentiation of crops in a Mediterranean climate. Five Landsat8 images covering the phenological stages of seven major crops types in the study area (Cape Winelands, South Africa) were acquired and processed. A statistical image fusion technique was used to enhance the spatial resolution of the imagery. The pan-sharpened imagery was used to produce a range of spectral features, textural measures, indices and colour transformations, after which it was segmented using the multi-resolution (MRS) algorithm. The entire set of 205 featu...