Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Don Mitchell Wilkes"'
Publikováno v:
Med Phys
Purpose One popular method of assessing brain functional connectivity (FC) is through seed-based correlation (SCA) analysis. One drawback of this method is when the seed location is varied slightly, the FC can vary dramatically. We propose a method s
Publikováno v:
IEEE Trans Med Imaging
Effective tissue clutter filtering is critical for non-contrast ultrasound imaging of slow blood flow in small vessels. Independent component analysis (ICA) has been considered by other groups for ultrasound clutter filtering in the past and was show
Autor:
Baxter P. Rogers, John C. Gore, Victoria L. Morgan, Arabinda Mishra, Zhaoyue Shi, Don Mitchell Wilkes, Li Min Chen
Publikováno v:
Human Brain Mapping. 37:3897-3910
Variations over time in resting-state correlations in blood oxygenation level-dependent (BOLD) signals from different cortical areas may indicate changes in brain functional connectivity. However, apparent variations over time may also arise from sta
Publikováno v:
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment ISBN: 9789811392160
In this chapter, we present a fast minimum spanning tree-based clustering algorithm for image segmentation and object recognition tasks. We begin with an introduction to the concept of the minimum spanning tree in general and its application to clust
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c354c6fbd40de0a55202544082684541
https://doi.org/10.1007/978-981-13-9217-7_8
https://doi.org/10.1007/978-981-13-9217-7_8
Publikováno v:
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment ISBN: 9789811392160
Being a crucial and challenging problem in computer vision, image segmentation refers to partitioning an image into several disjoint subsets such that each subset corresponds to a meaningful part of the image and is the very first step for recognizin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::304d59bfdf8a61b0b272c1594fe07ddd
https://doi.org/10.1007/978-981-13-9217-7_11
https://doi.org/10.1007/978-981-13-9217-7_11
Publikováno v:
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment ISBN: 9789811392160
The goal of machine learning research is to equip robots with human-like perception capabilities so that they can sense its working environment, understand the collected data, take appropriate actions, and learn from its experience so as to enhance f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c51339344697d33d529d52fca2c69ba4
https://doi.org/10.1007/978-981-13-9217-7_3
https://doi.org/10.1007/978-981-13-9217-7_3
Publikováno v:
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment ISBN: 9789811392160
The purpose of this chapter is to introduce in a fairly concise manner the key ideas underlying the field of unsupervised learning from the perspective of clustering for image segmentation tasks. We begin with a briefly review of fundamental concepts
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d6c8fcc7ac8f0e221fa20d9ee098ec8
https://doi.org/10.1007/978-981-13-9217-7_4
https://doi.org/10.1007/978-981-13-9217-7_4
Publikováno v:
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment ISBN: 9789811392160
In general, traditional machine learning algorithms typically employ task-specific methods and only the parameters pre-determined by the human programmer are updated. These methods often fail to respond to the dynamically changing states of the uncon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3667a667e9253182883d06526e03176f
https://doi.org/10.1007/978-981-13-9217-7_14
https://doi.org/10.1007/978-981-13-9217-7_14
Publikováno v:
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment ISBN: 9789811392160
With the development of computer vision, robots need to recognize targets from image sequences by supervised learning for autonomous navigation. To identify objects, the percept learning system of autonomous robots using unsupervised learning present
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74398719618428279ebc240c69ee8465
https://doi.org/10.1007/978-981-13-9217-7_9
https://doi.org/10.1007/978-981-13-9217-7_9