3,895 research outputs found
Historical forest biomass dynamics modelled with Landsat spectral trajectories
Acknowledgements National Forest Inventory data are available online, provided by Ministerio de Agricultura, Alimentación y Medio Ambiente (España). Landsat images are available online, provided by the USGS.Peer reviewedPostprin
k-Nearest Neighbour Classifiers: 2nd Edition (with Python examples)
Perhaps the most straightforward classifier in the arsenal or machine
learning techniques is the Nearest Neighbour Classifier -- classification is
achieved by identifying the nearest neighbours to a query example and using
those neighbours to determine the class of the query. This approach to
classification is of particular importance because issues of poor run-time
performance is not such a problem these days with the computational power that
is available. This paper presents an overview of techniques for Nearest
Neighbour classification focusing on; mechanisms for assessing similarity
(distance), computational issues in identifying nearest neighbours and
mechanisms for reducing the dimension of the data.
This paper is the second edition of a paper previously published as a
technical report. Sections on similarity measures for time-series, retrieval
speed-up and intrinsic dimensionality have been added. An Appendix is included
providing access to Python code for the key methods.Comment: 22 pages, 15 figures: An updated edition of an older tutorial on kN
Seeking Optimum System Settings for Physical Activity Recognition on Smartwatches
Physical activity recognition (PAR) using wearable devices can provide valued
information regarding an individual's degree of functional ability and
lifestyle. In this regards, smartphone-based physical activity recognition is a
well-studied area. Research on smartwatch-based PAR, on the other hand, is
still in its infancy. Through a large-scale exploratory study, this work aims
to investigate the smartwatch-based PAR domain. A detailed analysis of various
feature banks and classification methods are carried out to find the optimum
system settings for the best performance of any smartwatch-based PAR system for
both personal and impersonal models. To further validate our hypothesis for
both personal (The classifier is built using the data only from one specific
user) and impersonal (The classifier is built using the data from every user
except the one under study) models, we tested single subject validation process
for smartwatch-based activity recognition.Comment: 15 pages, 2 figures, Accepted in CVC'1
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