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Nishtha Srivastava
Nishtha Srivastava
Frankfurt Institute for Advanced Studies
Verified email at fias.uni-frankfurt.de - Homepage
Title
Cited by
Cited by
Year
Earthquake scenario in West Bengal with emphasis on seismic hazard microzonation of the city of Kolkata, India
SK Nath, MD Adhikari, SK Maiti, N Devaraj, N Srivastava, LD Mohapatra
Natural Hazards and Earth System Sciences 14 (9), 2549-2575, 2014
802014
Earthquake induced liquefaction hazard, probability and risk assessment in the city of Kolkata, India: its historical perspective and deterministic scenario
SK Nath, N Srivastava, C Ghatak, MD Adhikari, A Ghosh, SP Sinha Ray
Journal of Seismology 22, 35-68, 2018
352018
CREIME: A Convolutional Recurrent model for Earthquake Identification and Magnitude Estimation
M Chakraborty, D Fenner, W Li, J Faber, K Zhou, G Ruempker, H Stoecker, ...
https://arxiv.org/abs/2204.02924, 2022
262022
Probabilistic seismic hazard model of West Bengal, India
SK Maiti, SK Nath, MD Adhikari, N Srivastava, P Sengupta, AK Gupta
Journal of Earthquake Engineering 21 (7), 1113-1157, 2017
262017
EPick: Attention-based multi-scale UNet for earthquake detection and seismic phase picking
W Li, M Chakraborty, D Fenner, J Faber, K Zhou, G Rümpker, H Stöcker, ...
Frontiers in Earth Science 10, 953007, 2022
192022
A study on the effect of input data length on a deep-learning-based magnitude classifier
M Chakraborty, W Li, J Faber, G Rümpker, H Stoecker, N Srivastava
Solid Earth 13 (11), 1721-1729, 2022
92022
EPick: Multi-Class Attention-based U-shaped Neural Network for Earthquake Detection and Seismic Phase Picking
W Li, M Chakraborty, D Fenner, J Faber, K Zhou, G Ruempker, H Stoecker, ...
arXiv preprint arXiv:2109.02567, 2021
92021
A study on small magnitude seismic phase identification using 1D deep residual neural network
W Li, M Chakraborty, Y Sha, K Zhou, J Faber, G Rümpker, H Stöcker, ...
Artificial Intelligence in Geosciences 3, 115-122, 2022
82022
PolarCAP–A deep learning approach for first motion polarity classification of earthquake waveforms
M Chakraborty, CQ Cartaya, W Li, J Faber, G Rümpker, H Stoecker, ...
Artificial Intelligence in Geosciences 3, 46-52, 2022
82022
Automated seismo-volcanic event detection applied to stromboli (Italy)
D Fenner, G Rümpker, W Li, M Chakraborty, J Faber, J Köhler, H Stöcker, ...
Frontiers in Earth Science 10, 809037, 2022
82022
Deep Learning-based Small Magnitude Earthquake Detection and Seismic Phase Classification
W Li, Y Sha, K Zhou, J Faber, G Ruempker, H Stoecker, N Srivastava
https://arxiv.org/abs/2204.02870, 2022
62022
Real-time Earthquake Monitoring using Deep Learning: a case study on Turkey Earthquake Aftershock Sequence
W Li, J Koehler, M Chakraborty, C Quinteros-Cartaya, G Ruempker, ...
arXiv preprint arXiv:2211.09539, 2022
4*2022
Earthquake monitoring using deep learning with a case study of the Kahramanmaras Turkey earthquake aftershock sequence
W Li, M Chakraborty, J Köhler, C Quinteros-Cartaya, G Rümpker, ...
Solid Earth 15 (2), 197-213, 2024
32024
Testing the Potential of Deep Learning in Earthquake Forecasting
J Köhler, W Li, J Faber, G Rümpker, N Srivastava
EGU General Assembly Conference Abstracts, 3569, 2024
32024
Volcano-seismic event classification using wavelet scattering transforms
P Laumann, N Srivastava, W Li, G Ruempker
EGU General Assembly Conference Abstracts, EGU-17117, 2023
32023
Real time magnitude classification of earthquake waveforms using deep learning
M Chakraborty, G Rümpker, H Stöcker, W Li, J Faber, D Fenner, K Zhou, ...
EGU general assembly conference abstracts, EGU21-15941, 2021
32021
Mca-unet: Multi-class attention-aware u-net for seismic phase picking
W Li, G Rümpker, H Stöcker, M Chakraborty, D Fenner, J Faber, K Zhou, ...
EGU general assembly conference abstracts, EGU21-15841, 2021
32021
Exploring a CNN Model for Earthquake Magnitude Estimation using HR-GNSS data
CQ Cartaya, J Koehler, W Li, J Faber, N Srivastava
arXiv preprint arXiv:2304.09912, 2023
22023
Sunda-arc seismicity: continuing increase of high-magnitude earthquakes since 2004
N Srivastava, J Köhler, FA Nava, O El Sayed, M Chakraborty, ...
https://arxiv.org/abs/2108.06557, 2021
22021
SAIPy: A Python package for single-station earthquake monitoring using deep learning
W Li, M Chakraborty, CQ Cartaya, J Köhler, J Faber, MA Meier, ...
Computers & Geosciences 192, 105686, 2024
12024
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