Sensor-based and vision-based human activity recognition: A comprehensive survey
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …
of sensing devices, including vision sensors and embedded sensors, has motivated the …
A survey on deep learning for human activity recognition
Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …
home. In this study, we provide a comprehensive survey on recent advances and challenges …
Continuous human activity classification from FMCW radar with Bi-LSTM networks
A Shrestha, H Li, J Le Kernec… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Recognition of human movements with radar for ambient activity monitoring is a developed
area of research that yet presents outstanding challenges to address. In real environments …
area of research that yet presents outstanding challenges to address. In real environments …
Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach
OB Sezer, AM Ozbayoglu - Applied Soft Computing, 2018 - Elsevier
Computational intelligence techniques for financial trading systems have always been quite
popular. In the last decade, deep learning models start getting more attention, especially …
popular. In the last decade, deep learning models start getting more attention, especially …
Radar-based human-motion recognition with deep learning: Promising applications for indoor monitoring
Deep learning (DL) has shown tremendous promise in radar applications that involve target
classification and imaging. In the field of indoor monitoring, researchers have shown an …
classification and imaging. In the field of indoor monitoring, researchers have shown an …
A survey of deep learning-based human activity recognition in radar
Radar, as one of the sensors for human activity recognition (HAR), has unique
characteristics such as privacy protection and contactless sensing. Radar-based HAR has …
characteristics such as privacy protection and contactless sensing. Radar-based HAR has …
Autoencoders and their applications in machine learning: a survey
Autoencoders have become a hot researched topic in unsupervised learning due to their
ability to learn data features and act as a dimensionality reduction method. With rapid …
ability to learn data features and act as a dimensionality reduction method. With rapid …
Hand-gesture recognition using two-antenna Doppler radar with deep convolutional neural networks
S Skaria, A Al-Hourani, M Lech… - IEEE Sensors …, 2019 - ieeexplore.ieee.org
Low-cost consumer radar integrated circuits combined with recent advances in machine
learning have opened up a range of new possibilities in smart sensing. In this paper, we use …
learning have opened up a range of new possibilities in smart sensing. In this paper, we use …
Toward data anomaly detection for automated structural health monitoring: Exploiting generative adversarial nets and autoencoders
J Mao, H Wang, BF Spencer Jr - Structural Health Monitoring, 2021 - journals.sagepub.com
Damage detection is one of the most important tasks for structural health monitoring of civil
infrastructure. Before a damage detection algorithm can be applied, the integrity of the data …
infrastructure. Before a damage detection algorithm can be applied, the integrity of the data …
Deep learning-based anomaly detection in video surveillance: A survey
Anomaly detection in video surveillance is a highly developed subject that is attracting
increased attention from the research community. There is great demand for intelligent …
increased attention from the research community. There is great demand for intelligent …