Deep learning for time series classification and extrinsic regression: A current survey
Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …
learning tasks. Deep learning has revolutionized natural language processing and computer …
[HTML][HTML] Trends in human activity recognition with focus on machine learning and power requirements
The advancement and availability of technology can be employed to improve our daily lives.
One example is Human Activity Recognition (HAR). HAR research has been mainly …
One example is Human Activity Recognition (HAR). HAR research has been mainly …
PMLB: a large benchmark suite for machine learning evaluation and comparison
Background The selection, development, or comparison of machine learning methods in
data mining can be a difficult task based on the target problem and goals of a particular …
data mining can be a difficult task based on the target problem and goals of a particular …
Deep PPG: Large-scale heart rate estimation with convolutional neural networks
Photoplethysmography (PPG)-based continuous heart rate monitoring is essential in a
number of domains, eg, for healthcare or fitness applications. Recently, methods based on …
number of domains, eg, for healthcare or fitness applications. Recently, methods based on …
Approximated and user steerable tSNE for progressive visual analytics
Progressive Visual Analytics aims at improving the interactivity in existing analytics
techniques by means of visualization as well as interaction with intermediate results. One …
techniques by means of visualization as well as interaction with intermediate results. One …
Deepeyes: Progressive visual analytics for designing deep neural networks
Deep neural networks are now rivaling human accuracy in several pattern recognition
problems. Compared to traditional classifiers, where features are handcrafted, neural …
problems. Compared to traditional classifiers, where features are handcrafted, neural …
Felix: Fast and energy-efficient logic in memory
The Internet of Things (IoT) has led to the emergence of big data. Processing this amount of
data poses a challenge for current computing systems. PIM enables in-place computation …
data poses a challenge for current computing systems. PIM enables in-place computation …
HARTH: a human activity recognition dataset for machine learning
Existing accelerometer-based human activity recognition (HAR) benchmark datasets that
were recorded during free living suffer from non-fixed sensor placement, the usage of only …
were recorded during free living suffer from non-fixed sensor placement, the usage of only …
A movement decomposition and machine learning-based fall detection system using wrist wearable device
T De Quadros, AE Lazzaretti… - IEEE Sensors …, 2018 - ieeexplore.ieee.org
Falls in the elderly is a world health problem. Although many fall detection solutions were
presented in literature, few of them are wrist-wearable devices, mainly due to typical …
presented in literature, few of them are wrist-wearable devices, mainly due to typical …
A systematic review of wearable sensors for monitoring physical activity
This article reviews the use of wearable sensors for the monitoring of physical activity (PA)
for different purposes, including assessment of gait and balance, prevention and/or …
for different purposes, including assessment of gait and balance, prevention and/or …