4 citations · 8 across the 4 of their papers we have counts for
6 papers
Multi-Channel Time-Series Person and Soft-Biometric Identification
Nilah Ravi Nair, Fernando Moya Rueda, Christopher Reining +1
Multi-channel time-series datasets are popular in the context of human activity recognition (HAR). On-body device (OBD) recordings of human movements are often preferred for HAR ap…
Dataset Bias in Human Activity Recognition
Nilah Ravi Nair, Lena Schmid, Fernando Moya Rueda +3
When creating multi-channel time-series datasets for Human Activity Recognition (HAR), researchers are faced with the issue of subject selection criteria. It is unknown what physic…
Video-based Pose-Estimation Data as Source for Transfer Learning in Human Activity Recognition
Shrutarv Awasthi, Fernando Moya Rueda, Gernot A. Fink
Human Activity Recognition (HAR) using on-body devices identifies specific human actions in unconstrained environments. HAR is challenging due to the inter and intra-variance of hu…
Human Activity Recognition using Attribute-Based Neural Networks and Context Information
Stefan Lüdtke, Fernando Moya Rueda, Waqas Ahmed +2
We consider human activity recognition (HAR) from wearable sensor data in manual-work processes, like warehouse order-picking. Such structured domains can often be partitioned into…
Learning Attribute Representation for Human Activity Recognition
Fernando Moya Rueda, Gernot A. Fink
Attribute representations became relevant in image recognition and word spotting, providing support under the presence of unbalance and disjoint datasets. However, for human activi…
Neuron Pruning for Compressing Deep Networks using Maxout Architectures
Fernando Moya Rueda, Rene Grzeszick, Gernot A. Fink
This paper presents an efficient and robust approach for reducing the size of deep neural networks by pruning entire neurons. It exploits maxout units for combining neurons into mo…