most citedUnsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout

89 citations · 149 across the 5 of their papers we have counts for

collaborators

5 papers

cs.ET2019★ 3 cited

Mapping Spiking Neural Networks to Neuromorphic Hardware

Adarsha Balaji, Anup Das, Yuefeng Wu +7

Neuromorphic hardware platforms implement biological neurons and synapses to execute spiking neural networks (SNNs) in an energy-efficient manner. We present SpiNeMap, a design met…

q-bio.NC2019★ 57 cited

Mapping of Local and Global Synapses on Spiking Neuromorphic Hardware

Anup Das, Yuefeng Wu, Khanh Huynh +3

Spiking Neural Networks (SNNs) are widely deployed to solve complex pattern recognition, function approximation and image classification tasks. With the growing size and complexity…

eess.SP2019

Heartbeat Classification in Wearables Using Multi-layer Perceptron and Time-Frequency Joint Distribution of ECG

Anup Das, Francky Catthoor, Siebren Schaafsma

Heartbeat classification using electrocardiogram (ECG) data is a vital assistive technology for wearable health solutions. We propose heartbeat feature classification based on a no…

cs.CV2019

LocalNorm: Robust Image Classification through Dynamically Regularized Normalization

Bojian Yin, Siebren Schaafsma, Henk Corporaal +2

While modern convolutional neural networks achieve outstanding accuracy on many image classification tasks, they are, compared to humans, much more sensitive to image degradation.…

cs.NE2017★ 89 cited

Unsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout

Anup Das, Paruthi Pradhapan, Willemijn Groenendaal +7

Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine intelligent approach for heart-rate estimation from electrocardiogram…