Results 21 to 30 of about 2,288,890 (272)
Daily Human Activity Recognition Using Non-Intrusive Sensors
Sensors, 2021 In recent years, Artificial Intelligence Technologies (AIT) have been developed to improve the quality of life of the elderly and their safety in the home.
Raúl Gómez Ramos +3 more
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Fast human activity recognition based on structure and motion [PDF]
, 2011 This is the post-print version of the final paper published in Pattern Recognition Letters. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural ...
Boulgouris, NV, Hu, J
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Human activity recognition system
2023 International Conference on Computational Intelligence, Communication Technology and Networking (CICTN), 2023 Abstract: Almost every university has its management system to manage the students' records. Currently, even though there is a student management system that manages the students' records in Universiti Malaysia Sarawak (UNIMAS), no permission is provided for lecturers to access the system. This is because the access permission is only to top management
Divaksh Parmar +4 more
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Sensor-Based Open-Set Human Activity Recognition Using Representation Learning With Mixup Triplets
IEEE Access, 2022 The main objective of sensor-based human activity recognition (HAR) is to classify predefined human physical activities with multichannel signals acquired from wearable sensors.
Minjung Lee, Seoung Bum Kim
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Human activity recognition making use of long short-term memory techniques [PDF]
, 2019 The optimisation and validation of a classifiers performance when applied to real world problems is not always effectively shown. In much of the literature describing the application of artificial neural network architectures to Human Activity ...
Shenfield, Alex, Wainwright, Richard
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Deep convolutional and LSTM recurrent neural networks for multimodal wearable activity recognition [PDF]
, 2016 Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor ...
Alsheikh +11 more
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Sensors, 2016 Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services.
Hiram Ponce +2 more
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Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention [PDF]
, 2018 Deep neural networks, including recurrent networks, have been successfully applied to human activity recognition. Unfortunately, the final representation learned by recurrent networks might encode some noise (irrelevant signal components, unimportant ...
Gao, Haoxiang +6 more
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Comparing CNN and Human Crafted Features for Human Activity Recognition [PDF]
, 2019 Deep learning techniques such as Convolutional Neural Networks (CNNs) have shown good results in activity recognition. One of the advantages of using these methods resides in their ability to generate features automatically.
Chen, Liming +9 more
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Physical Human Activity Recognition Using Wearable Sensors
Sensors, 2015 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 study and were worn by healthy subjects at key points of upper/lower ...
Ferhat Attal +5 more
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