Skip to main navigation
Skip to search
Skip to main content
University of Engineering and Technology - UTEC Home
Español
English
Search content at University of Engineering and Technology - UTEC
Home
Profiles
Research units
Equipment
Projects
Research output
Student theses
Time-series visual representations for sleep stages classification
Rebeca Padovani Ederli
, Didier A. Vega-Oliveros
,
Aurea Soriano-Vargas
, Anderson Rocha
, Zanoni Dias
Department of Computer Science
University of Engineering and Technology - UTEC
Research output
:
Contribution to journal
›
Article
›
peer-review
1
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Time-series visual representations for sleep stages classification'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Engineering
Gramian Angular Field
100%
Raw Data
50%
Two Dimensional
50%
Data Series
50%
Classification Accuracy
50%
Collected Data
50%
Spectrogram
50%
Classification Task
50%
Convolutional Neural Network
50%
Classification Performance
50%
Artificial Intelligence Technique
50%
Continuous Data
50%
Health Monitoring
50%
Effective Approach
50%
Home Environment
50%
Extracted Feature
50%
Multiple Sensor
50%
Computer Science
Visual Representation
100%
Classification Stage
100%
Traditional Method
22%
Convolutional Neural Network
11%
Continuous Data
11%
Classification Accuracy
11%
Superior Performance
11%
Classification Task
11%
Artificial Intelligence
11%
Classification Performance
11%
Extracted Feature
11%
Effective Approach
11%
Multiple Sensor
11%
Home Environment
11%
Ensemble Method
11%
Time Series Data
11%
Agricultural and Biological Sciences
Artificial Intelligence
100%
Neural Network
100%
Earth and Planetary Sciences
Time Series
100%
Accelerometer
33%
Artificial Intelligence
33%
Spectrogram
33%