A survey on video-based human action recognition: recent updates, datasets, challenges, and applications
Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …
Human action recognition: A taxonomy-based survey, updates, and opportunities
Human action recognition systems use data collected from a wide range of sensors to
accurately identify and interpret human actions. One of the most challenging issues for …
accurately identify and interpret human actions. One of the most challenging issues for …
Toyota smarthome: Real-world activities of daily living
The performance of deep neural networks is strongly influenced by the quantity and quality
of annotated data. Most of the large activity recognition datasets consist of data sourced from …
of annotated data. Most of the large activity recognition datasets consist of data sourced from …
Pulmonary COVID-19: learning spatiotemporal features combining CNN and LSTM networks for lung ultrasound video classification
B Barros, P Lacerda, C Albuquerque, A Conci - Sensors, 2021 - mdpi.com
Deep Learning is a very active and important area for building Computer-Aided Diagnosis
(CAD) applications. This work aims to present a hybrid model to classify lung ultrasound …
(CAD) applications. This work aims to present a hybrid model to classify lung ultrasound …
Deep learning and RGB-D based human action, human–human and human–object interaction recognition: A survey
Human activity recognition is one of the most studied topics in the field of computer vision. In
recent years, with the availability of RGB-D sensors and powerful deep learning techniques …
recent years, with the availability of RGB-D sensors and powerful deep learning techniques …
Integration of deep learning into the iot: A survey of techniques and challenges for real-world applications
The internet of things (IoT) has emerged as a pivotal technological paradigm facilitating
interconnected and intelligent devices across multifarious domains. The proliferation of IoT …
interconnected and intelligent devices across multifarious domains. The proliferation of IoT …
DTR-HAR: deep temporal residual representation for human activity recognition
Human activity recognition (HAR) is a highly prized application in the pattern recognition
and the computer vision fields. Up till now, deep neural networks have acquired big attention …
and the computer vision fields. Up till now, deep neural networks have acquired big attention …
Switching structured prediction for simple and complex human activity recognition
Automatic human activity recognition is an integral part of any interactive application
involving humans (eg, human–robot interaction systems). One of the main challenges for …
involving humans (eg, human–robot interaction systems). One of the main challenges for …
Improved action recognition with separable spatio-temporal attention using alternative skeletal and video pre-processing
P Climent-Perez, F Florez-Revuelta - Sensors, 2021 - mdpi.com
The potential benefits of recognising activities of daily living from video for active and
assisted living have yet to be fully untapped. These technologies can be used for behaviour …
assisted living have yet to be fully untapped. These technologies can be used for behaviour …
融入注意力机制的深度学习动作识别.
张宇， 张雷 - Telecommunication Engineering, 2021 - search.ebscohost.com
针对现有的深度学习方法在人体动作识别中易出现过拟合, 易受到干扰信息影响,
特征表达能力不足的问题, 提出了一种融入注意力机制的深度学习动作识别方法 …
特征表达能力不足的问题, 提出了一种融入注意力机制的深度学习动作识别方法 …