DARWIN: A Framework for Machine Learning and Computer Vision Research and Development

被引：0
|
作者：
Gould, Stephen [1 ]
机构：
[1] Australian Natl Univ, Res Sch Comp Sci, Canberra, ACT 0200, Australia
来源：
JOURNAL OF MACHINE LEARNING RESEARCH | 2012年 / 13卷
关键词：
machine learning; graphical models; computer vision; open-source software; APPROXIMATE INFERENCE;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We present an open-source platform-independent C++ framework for machine learning and computer vision research. The framework includes a wide range of standard machine learning and graphical models algorithms as well as reference implementations for many machine learning and computer vision applications. The framework contains Matlab wrappers for core components of the library and an experimental graphical user interface for developing and visualizing machine learning data flows.
引用
收藏
页码：3533 / 3537
页数：5
相关论文
共 50 条
  • [1] Machine Learning in Computer Vision
    Khan, Asharul Islam
    Al-Habsi, Salim
    [J]. INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE, 2020, 167 : 1444 - 1451
  • [2] Machine learning in computer vision
    Esposito, F
    Malerba, D
    [J]. APPLIED ARTIFICIAL INTELLIGENCE, 2001, 15 (08) : 693 - 705
  • [3] An Analytical Framework for Trusted Machine Learning and Computer Vision Running with Blockchain
    Wang, Tao
    Du, Maggie
    Wu, Xinmin
    He, Taiping
    [J]. 2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2020), 2020, : 32 - 38
  • [4] Machine Learning in Computer Vision: A Review
    Khan, Abdullah Ayub
    Laghari, Asif Ali
    Awan, Shafique Ahmed
    [J]. EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS, 2021, 8 (32): : 1 - 11
  • [5] Computer vision and machine learning for phenotyping
    Steibel, J.
    [J]. JOURNAL OF DAIRY SCIENCE, 2022, 105 : 98 - 99
  • [6] Research on computer vision enhancement in intelligent robot based on machine learning and deep learning
    Ding, Yuhan
    Hua, Lisha
    Li, Shunlei
    [J]. NEURAL COMPUTING & APPLICATIONS, 2022, 34 (04): : 2623 - 2635
  • [7] Research on computer vision enhancement in intelligent robot based on machine learning and deep learning
    Yuhan Ding
    Lisha Hua
    Shunlei Li
    [J]. Neural Computing and Applications, 2022, 34 : 2623 - 2635
  • [8] Research on Some Key Problems of Machine Learning in Computer Vision and Cancer Bioinformatics
    Liu, Haiyan
    Fan, Yunxia
    [J]. BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2020, 127 : 181 - 181
  • [9] International conference on computer vision and machine learning
    Rambabu, Sri Kommareddy
    [J]. Journal of Physics: Conference Series, 2019, 1228 (01)
  • [10] ADVANCED MACHINE LEARNING TECHNIQUES FOR COMPUTER VISION
    MOSCATELLI, S
    KODRATOFF, Y
    [J]. LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, 1992, 617 : 161 - 197
12345