scholarly journals Classification of Indian Classical Music with Time-Series Matching using Deep Learning

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Akhilesh Kumar Sharma ◽  
Gaurav Aggarwal ◽  
Sachit Bhardwaj ◽  
Prasun Chakrabarti ◽  
Tulika Chakrabarti ◽  
...  
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Classical Music ◽  
Indian Classical Music

scholarly journals Classification of chaotic time series with deep learning

2020 ◽  
Vol 403 ◽  
pp. 132261 ◽  
Author(s):  
Nicolas Boullé ◽  
Vassilios Dallas ◽  
Yuji Nakatsukasa ◽  
D. Samaddar
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Chaotic Time Series

scholarly journals Deep learning classification of temporal data in ecology

2020 ◽  
Author(s):  
César Capinha ◽  
Ana Ceia-Hasse ◽  
Andrew M. Kramer ◽  
Christiaan Meijer
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Data ◽  
Meteorological Data ◽  
Species Distribution Modelling ◽  
Series Data ◽  
Temporal Data ◽  
Climate Time Series ◽  
Biological Entities

AbstractTemporal data is ubiquitous in ecology and ecologists often face the challenge of accurately differentiating these data into predefined classes, such as biological entities or ecological states. The usual approach transforms the temporal data into static predictors of the classes. However, recent deep learning techniques can perform the classification using raw time series, eliminating subjective and resource-consuming data transformation steps, and potentially improving classification results. We present a general approach for time series classification that considers multiple deep learning algorithms and illustrate it with three case studies: i) insect species identification from wingbeat spectrograms; ii) species distribution modelling from climate time series and iii) the classification of phenological phases from continuous meteorological data. The deep learning approach delivered ecologically sensible and accurate classifications, proving its potential for wide applicability across subfields of ecology. We recommend deep learning as an alternative to techniques requiring the transformation of time series data.

Deep Learning-based Approach for Classification of Tribological Time Series Data for Hand Creams

2021 ◽  
Vol 44 (3) ◽  
pp. 98-105
Author(s):  
Ji Won Kim ◽  
◽  
You Min Lee ◽  
Shawn Han ◽  
Kyeongtaek Kim
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Data ◽  
Series Data

scholarly journals Deep learning for classification of time series spectral images using combined multi-temporal and spectral features

2021 ◽  
Vol 1143 ◽  
pp. 9-20
Author(s):  
Jun-Li Xu ◽  
Siewert Hugelier ◽  
Hongyan Zhu ◽  
Aoife A. Gowen
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Spectral Features ◽  
Multi Temporal

Raga Recognition in Indian Classical Music Using Deep Learning

2021 ◽  
pp. 248-263
Author(s):  
Devansh P. Shah ◽  
Nikhil M. Jagtap ◽  
Prathmesh T. Talekar ◽  
Kiran Gawande
Keyword(s):  
Deep Learning ◽  
Classical Music ◽  
Indian Classical Music

scholarly journals Classification of short time series in early Parkinsons disease with deep learning of fuzzy recurrence plots

2019 ◽  
Vol 6 (6) ◽  
pp. 1306-1317 ◽  
Author(s):  
Tuan D. Pham ◽  
Karin Wardell ◽  
Anders Eklund ◽  
Goran Salerud
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Recurrence Plots ◽  
Short Time Series ◽  
Parkinsons Disease ◽  
Short Time
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