AIMC Topic: Human Activities

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On the Post Hoc Explainability of Optimized Self-Organizing Reservoir Network for Action Recognition.

Sensors (Basel, Switzerland) Mar 1, 2022
This work proposes a novel unsupervised self-organizing network, called the Self-Organizing Convolutional Echo State Network (SO-ConvESN), for learning node centroids and interconnectivity maps compatible with the deterministic initialization of Echo...
Humans Neural Networks, Computer Human Activities Recognition, Psychology Learning Algorithms
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Improving Radar Human Activity Classification Using Synthetic Data with Image Transformation.

Sensors (Basel, Switzerland) Feb 16, 2022
Machine Learning (ML) methods have become state of the art in radar signal processing, particularly for classification tasks (e.g., of different human activities). Radar classification can be tedious to implement, though, due to the limited size and ...
Algorithms Machine Learning Radar Human Activities Humans Neural Networks, Computer
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Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances.

Sensors (Basel, Switzerland) Feb 14, 2022
Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human-computer interaction, that measure and improve our daily lives. Many of these applications are made possible by leveraging the...
Deep Learning Wearable Electronic Devices Humans Human Activities
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3DMesh-GAR: 3D Human Body Mesh-Based Method for Group Activity Recognition.

Sensors (Basel, Switzerland) Feb 14, 2022
Group activity recognition is a prime research topic in video understanding and has many practical applications, such as crowd behavior monitoring, video surveillance, etc. To understand the multi-person/group action, the model should not only identi...
Neural Networks, Computer Human Body Humans Surgical Mesh Skeleton Human Activities
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Comparing Sampling Strategies for Tackling Imbalanced Data in Human Activity Recognition.

Sensors (Basel, Switzerland) Feb 11, 2022
Human activity recognition (HAR) using wearable sensors is an increasingly active research topic in machine learning, aided in part by the ready availability of detailed motion capture data from smartphones, fitness trackers, and smartwatches. The go...
Human Activities Machine Learning Humans Cluster Analysis Algorithms
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Automated Detection of Rehabilitation Exercise by Stroke Patients Using 3-Layer CNN-LSTM Model.

Journal of healthcare engineering Feb 4, 2022
According to statistics, stroke is the second or third leading cause of death and adult disability. Stroke causes losing control of the motor function, paralysis of body parts, and severe back pain for which a physiotherapist employs many therapies t...
Neural Networks, Computer Algorithms Humans Human Activities Exercise Therapy Stroke
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Human Activity and Motion Pattern Recognition within Indoor Environment Using Convolutional Neural Networks Clustering and Naive Bayes Classification Algorithms.

Sensors (Basel, Switzerland) Jan 28, 2022
Human Activity Recognition (HAR) systems are designed to read sensor data and analyse it to classify any detected movement and respond accordingly. However, there is a need for more responsive and near real-time systems to distinguish between false a...
Cluster Analysis Human Activities Bayes Theorem Humans Algorithms Neural Networks, Computer
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Human Activity Recognition Based on Residual Network and BiLSTM.

Sensors (Basel, Switzerland) Jan 14, 2022
Due to the wide application of human activity recognition (HAR) in sports and health, a large number of HAR models based on deep learning have been proposed. However, many existing models ignore the effective extraction of spatial and temporal featur...
Human Activities Humans Running Deep Learning Walking Neural Networks, Computer
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3-D Deconvolutional Networks for the Unsupervised Representation Learning of Human Motions.

IEEE transactions on cybernetics Jan 11, 2022
Data representation learning is one of the most important problems in machine learning. Unsupervised representation learning becomes meritorious as it has no necessity of label information with observed data. Due to the highly time-consuming learning...
Human Activities Humans Machine Learning Neural Networks, Computer
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Using a Selective Ensemble Support Vector Machine to Fuse Multimodal Features for Human Action Recognition.

Computational intelligence and neuroscience Jan 10, 2022
The traditional human action recognition (HAR) method is based on RGB video. Recently, with the introduction of Microsoft Kinect and other consumer class depth cameras, HAR based on RGB-D (RGB-Depth) has drawn increasing attention from scholars and i...
Algorithms Humans Human Activities Motion Support Vector Machine Pattern Recognition, Automated
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