Deep learning for time series classification and extrinsic regression: A current survey
Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …
learning tasks. Deep learning has revolutionized natural language processing and computer …
A substrate-less nanomesh receptor with meta-learning for rapid hand task recognition
With the help of machine learning, electronic devices—including electronic gloves and
electronic skins—can track the movement of human hands and perform tasks such as object …
electronic skins—can track the movement of human hands and perform tasks such as object …
An empirical survey of data augmentation for time series classification with neural networks
In recent times, deep artificial neural networks have achieved many successes in pattern
recognition. Part of this success can be attributed to the reliance on big data to increase …
recognition. Part of this success can be attributed to the reliance on big data to increase …
Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion
Unsupervised/self-supervised time series representation learning is a challenging problem
because of its complex dynamics and sparse annotations. Existing works mainly adopt the …
because of its complex dynamics and sparse annotations. Existing works mainly adopt the …
An efficient multi-scale CNN model with intrinsic feature integration for motor imagery EEG subject classification in brain-machine interfaces
AM Roy - Biomedical Signal Processing and Control, 2022 - Elsevier
Objective Electroencephalogram (EEG) based motor imagery (MI) classification is an
important aspect in brain-machine interfaces (BMIs) which bridges between neural system …
important aspect in brain-machine interfaces (BMIs) which bridges between neural system …
Data augmentation for time-series classification: An extensive empirical study and comprehensive survey
Z Gao, H Liu, L Li - arxiv preprint arxiv:2310.10060, 2023 - arxiv.org
Data Augmentation (DA) has become a critical approach in Time Series Classification
(TSC), primarily for its capacity to expand training datasets, enhance model robustness …
(TSC), primarily for its capacity to expand training datasets, enhance model robustness …
PCovNet+: A CNN-VAE anomaly detection framework with LSTM embeddings for smartwatch-based COVID-19 detection
The world is slowly recovering from the Coronavirus disease 2019 (COVID-19) pandemic;
however, humanity has experienced one of its According to work by Mishra et al.(2020), the …
however, humanity has experienced one of its According to work by Mishra et al.(2020), the …
HMGAN: A hierarchical multi-modal generative adversarial network model for wearable human activity recognition
Wearable Human Activity Recognition (WHAR) is an important research field of ubiquitous
and mobile computing. Deep WHAR models suffer from the overfitting problem caused by …
and mobile computing. Deep WHAR models suffer from the overfitting problem caused by …
PCovNet: A presymptomatic COVID-19 detection framework using deep learning model using wearables data
While the advanced diagnostic tools and healthcare management protocols have been
struggling to contain the COVID-19 pandemic, the spread of the contagious viral pathogen …
struggling to contain the COVID-19 pandemic, the spread of the contagious viral pathogen …
Time series classification, augmentation and artificial-intelligence-enabled software for emergency response in freight transportation fires
In responding to freight transportation fire incidents, first responders refer to the terials
labeled on the freights and the Emergency Response Guidebook (ERG) for guidance on the …
labeled on the freights and the Emergency Response Guidebook (ERG) for guidance on the …