Results 51 to 60 of about 1,572,835 (188)

Towards Emotion Recognition: A Persistent Entropy Application

, 2018
Emotion recognition and classification is a very active area of research. In this paper, we present a first approach to emotion classification using persistent entropy and support vector machines. A topology-based model is applied to obtain a single real
A Geron, A Ortony, A Zomorodian, AS Popova, B Schuller, B Yang, C Cortes, D Ververidis, DM Howard, E Globerson, G Bredon, H Edelsbrunner, J Russell, K Pearson, L Wasserman, M Rucco, N Cristianini, SR Livingstone   +17 more
core   +1 more source

Signal + Context = Better Classification.

, 2007
[TODO] Add abstract here.
Jean-Julien Aucouturier, Pachet, François, Roy, Pierre, Beurivé, Anthony   +3 more
openaire   +1 more source

A symmetric adaptive visibility graph classification method of orthogonal signals for automatic modulation classification

IET Communications, 2023
Visibility graph methods allow time series to mine non‐Euclidean spatial features of sequences by using graph neural network algorithms. Unlike the traditional fixed‐rule‐based univariate time series visibility graph methods, a symmetric adaptive ...
Haihai Bai, Jingjing Yang, Ming Huang, Wenting Li   +3 more
doaj   +1 more source

Thresholding Wavelet Networks for Signal Classification [PDF]

International Journal of Wavelets, Multiresolution and Information Processing, 2003
This paper reports a new signal classification tool, a modified wavelet network called Thresholding Wavelet Networks (TWN). The network is designed for the purposes of classifying signals. The philosophy of the technique is that often the difference between signals may not lie in the spectral or temporal region where the signal strength is high ...
Pah, Nemuel Daniel, Kumar, Dinesh Kant
openaire   +3 more sources

Adversarial discriminative domain adaptation for modulation classification based on Ulam stability

IET Radar, Sonar & Navigation, 2023
Domain adaptation modulation classification aims to improve the cross‐domain robustness of modulation classification, with the basic idea of mitigating the domain shift between the label‐rich source domain and label‐poor target domain in the latent ...
Wenjuan Ren, Qian Chen, Zhanpeng Yang
doaj   +1 more source

A New Low SNR Underwater Acoustic Signal Classification Method Based on Intrinsic Modal Features Maintaining Dimensionality Reduction

Polish Maritime Research, 2020
The classification of low signal-to-noise ratio (SNR) underwater acoustic signals in complex acoustic environments and increasingly small target radiation noise is a hot research topic..
Ju Yang, Wei Zhengxian, Huangfu Li, Xiao Feng   +3 more
doaj   +1 more source

Wi-Fi-Enabled Vision via Spatially-Variant Pose Estimation Based on Convolutional Transformer Network

IEEE Access
Wi-Fi-enabled vision offers a transformative paradigm for non-optical pose estimation, particularly in occluded or privacy-sensitive environments where traditional visual systems falter.
Hyeon-Ju Lee, Seok-Jun Buu
doaj   +1 more source

Statistical Models of Reconstructed Phase Spaces for Signal Classification [PDF]

, 2006
This paper introduces a novel approach to the analysis and classification of time series signals using statistical models of reconstructed phase spaces.
Johnson, Michael T, Lindgren, Andrew C., Povinelli, Richard J., Roberts, Felice M., Ye, Jinjin   +4 more
core   +1 more source

Signal-dependent wavelets for electromyogram classification [PDF]

Medical & Biological Engineering & Computing, 2005
In the study, an efficient method to perform supervised classification of surface electromyogram (EMG) signals is proposed. The method is based on the choice of a relevant representation space and its optimisation with respect to a training set. As EMG signals are the summation of compact-support waveforms (the motor unit action potentials), a natural ...
Maitrot, A., Lucas, M.-F., Doncarli, C., Farina, Dario   +3 more
openaire   +3 more sources

Stealthy Adversarial Attacks on Machine Learning-Based Classifiers of Wireless Signals

IEEE Transactions on Machine Learning in Communications and Networking
Machine learning (ML) has been successfully applied to classification tasks in many domains, including computer vision, cybersecurity, and communications. Although highly accurate classifiers have been developed, research shows that these classifiers are,
Wenhan Zhang, Marwan Krunz, Gregory Ditzler   +2 more
doaj   +1 more source