[HTML][HTML] Physical human activity recognition using wearable sensors

F Attal, S Mohammed, M Dedabrishvili, F Chamroukhi… - Sensors, 2015 - mdpi.com
This paper presents a review of different classification techniques used to recognize human
activities from wearable inertial sensor data. Three inertial sensor units were used in this …

Sleep stage classification using EEG signal analysis: a comprehensive survey and new investigation

KAI Aboalayon, M Faezipour, WS Almuhammadi… - Entropy, 2016 - mdpi.com
Sleep specialists often conduct manual sleep stage scoring by visually inspecting the
patient's neurophysiological signals collected at sleep labs. This is, generally, a very difficult …

An introduction to domain adaptation and transfer learning

WM Kouw, M Loog - arxiv preprint arxiv:1812.11806, 2018 - arxiv.org
In machine learning, if the training data is an unbiased sample of an underlying distribution,
then the learned classification function will make accurate predictions for new samples …

[書籍][B] Practical machine learning for data analysis using python

A Subasi - 2020 - books.google.com
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for
creating real-world intelligent systems. It provides a comprehensive approach with concepts …

[書籍][B] Statistical pattern recognition

AR Webb - 2003 - books.google.com
Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

Medical image segmentation methods, algorithms, and applications

A Norouzi, MSM Rahim, A Altameem, T Saba… - IETE Technical …, 2014 - Taylor & Francis
Medical images have made a great impact on medicine, diagnosis, and treatment. The most
important part of image processing is image segmentation. Many image segmentation …

Revealing household characteristics from smart meter data

C Beckel, L Sadamori, T Staake, S Santini - Energy, 2014 - Elsevier
Utilities are currently deploying smart electricity meters in millions of households worldwide
to collect fine-grained electricity consumption data. We present an approach to automatically …

Classification of EEG signals based on pattern recognition approach

HU Amin, W Mumtaz, AR Subhani… - Frontiers in …, 2017 - frontiersin.org
Feature extraction is an important step in the process of electroencephalogram (EEG) signal
classification. The authors propose a “pattern recognition” approach that discriminates EEG …

EEG classification of ADHD and normal children using non-linear features and neural network

MR Mohammadi, A Khaleghi, AM Nasrabadi… - Biomedical Engineering …, 2016 - Springer
Abstract Purpose Attention-Deficit Hyperactivity Disorder (ADHD) is a neuro-developmental
disorder that is characterized by hyperactivity, inattention and abrupt behaviors. This study …

Acoustic side-channel attacks on additive manufacturing systems

MA Al Faruque, SR Chhetri… - 2016 ACM/IEEE 7th …, 2016 - ieeexplore.ieee.org
Additive manufacturing systems, such as 3D printers, emit sounds while creating objects.
Our work demonstrates that these sounds carry process information that can be used to …