Standout Papers

Data augmentation for deep-learning-based electroencephalography 2020 2026 2022 2024227
  1. Data augmentation for deep-learning-based electroencephalography (2020)
    Elnaz Lashgari, Uri Maoz et al. Journal of Neuroscience Methods

Immediate Impact

21 standout
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Citing Papers

Interpretable modulated differentiable STFT and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine transfer fault diagnosis under speed fluctuations
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Small data challenges for intelligent prognostics and health management: a review
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2 intermediate papers

Works of Elnaz Lashgari being referenced

Data augmentation for deep-learning-based electroencephalography
2020 Standout

Author Peers

Author Last Decade Papers Cites
Elnaz Lashgari 161 35 43 36 4 244
Nannapas Banluesombatkul 181 25 36 35 6 227
Xiaolin Hong 179 51 26 38 9 287
Hisham Alwanni 211 36 42 36 7 238
ML Akin 156 21 34 51 6 279
Trilok Chand 176 36 59 31 12 296
Ignas Martišius 184 20 33 41 10 224
Ashima Khosla 172 23 57 30 6 228
P. Bhuvaneswari 175 39 47 47 12 279
Xiaotong Gu 172 20 17 30 2 244
Alejandro Riera 162 26 23 23 7 214

All Works

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2026