Results 21 to 30 of about 14,335,879 (294)
Two-Stage Human Activity Recognition Using 2D-ConvNet.
International Journal of Interactive Multimedia and Artificial Intelligence, 2020 There is huge requirement of continuous intelligent monitoring system for human activity recognition in various domains like public places, automated teller machines or healthcare sector.
Kamal Kant Verma +3 more
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Human Activity Recognition with Meta-learning and Attention [PDF]
Jisuanji kexue, 2023 With the in-depth research of deep learning technology,its application and development in the field of behavior recognition have been greatly promoted.Current research on behavior recognition based on deep learning usually requires a large training data ...
WANG Jiahao, ZHONG Xin, LI Wenxiong, ZHAO Dexin
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RECOGNITION OF HUMAN ACTIVITY BY VIDEO DATA
International Journal of Advanced Studies, 2022 The paper considers the problem solution of classifying the type of physical activity of a person according to visual data. The authors propose using of deep neural networks to determine the type of activity.
Anna V. Pyataeva +3 more
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An Efficient Human Activity Recognition Technique Based on Deep Learning [PDF]
, 2019 In this paper, we present a new deep learning-based human activity recognition technique. First, we track and extract human body from each frame of the video stream. Next, we abstract human silhouettes and use them to create binary space-time maps (BSTMs)
KHELALEF, Aziz +5 more
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On attention models for human activity recognition [PDF]
Proceedings of the 2018 ACM International Symposium on Wearable Computers, 2018 Most approaches that model time-series data in human activity recognition based on body-worn sensing (HAR) use a fixed size temporal context to represent different activities. This might, however, not be apt for sets of activities with individ- ually varying durations.
Vishvak S. Murahari, Thomas Plötz
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Out-of-distribution in Human Activity Recognition
2022 Swedish Artificial Intelligence Society Workshop (SAIS), 2022 With the growing interest of the research community in making deep learning (DL) robust and reliable, detecting out-of-distribution (OOD) data has become critical. Detecting OOD inputs during test/prediction allows the model to account for discriminative features unknown to the model.
Roy,Debaditya +2 more
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Time Analysis in Human Activity Recognition
Neural Processing Letters, 2021 Continuous human activity recognition from inertial signals is performed by splitting these temporal signals into time windows and identifying the activity in each window. Defining the appropriate window duration has been the target of several previous works.
Gil Martín, Manuel +3 more
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A CSI-Based Multi-Environment Human Activity Recognition Framework
Applied Sciences, 2022 Passive human activity recognition (HAR) systems, in which no sensors are attached to the subject, provide great potentials compared to conventional systems.
Baha A. Alsaify +4 more
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Context-Aware Human Activity Recognition in Industrial Processes
Sensors, 2021 The automatic, sensor-based assessment of human activities is highly relevant for production and logistics, to optimise the economics and ergonomics of these processes.
Friedrich Niemann +3 more
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Boosting Inertial-Based Human Activity Recognition With Transformers
IEEE Access, 2021 Activity recognition problems such as human activity recognition and smartphone location recognition can improve the accuracy of different navigation or healthcare tasks, which rely solely on inertial sensors.
Yoli Shavit, Itzik Klein
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