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Found 6 papers, 0 papers with code
Multi-Channel Time-Series Person and Soft-Biometric Identification
On-body device (OBD) recordings of human movements are often preferred for HAR applications not only for their reliability but as an approach for identity protection, e. g., in industrial settings.
Dataset Bias in Human Activity Recognition
It is unknown what physical characteristics and/or soft-biometrics, such as age, height, and weight, need to be taken into account to train a classifier to achieve robustness towards heterogeneous populations in the training and testing data.
Video-based Pose-Estimation Data as Source for Transfer Learning in Human Activity Recognition
HAR is challenging due to the inter and intra-variance of human movements; moreover, annotated datasets from on-body devices are scarce.
Human Activity Recognition using Attribute-Based Neural Networks and Context Information
Here, we show how such context information can be integrated systematically into a deep neural network-based HAR system.
Learning Attribute Representation for Human Activity Recognition
Attribute representations became relevant in image recognition and word spotting, providing support under the presence of unbalance and disjoint datasets.
Neuron Pruning for Compressing Deep Networks using Maxout Architectures
Furthermore, it will be shown that neuron pruning can be combined with subsequent weight pruning, reducing the size of the LeNet-5 and VGG16 up to $92\%$ and $80\%$ respectively.
