Neda Rohani
Neda Rohani
Applied Scientist at Microsoft
Verified email at
Cited by
Cited by
Gravity Spy: integrating advanced LIGO detector characterization, machine learning, and citizen science
M Zevin, S Coughlin, S Bahaadini, E Besler, N Rohani, S Allen, M Cabero, ...
Classical and quantum gravity 34 (6), 064003, 2017
Machine learning for Gravity Spy: Glitch classification and dataset
S Bahaadini, V Noroozi, N Rohani, S Coughlin, M Zevin, JR Smith, ...
Information Sciences 444, 172-186, 2018
Classifying the unknown: discovering novel gravitational-wave detector glitches using similarity learning
S Coughlin, S Bahaadini, N Rohani, M Zevin, O Patane, M Harandi, ...
Physical Review D 99 (8), 082002, 2019
Innovative data reduction and visualization strategy for hyperspectral imaging datasets using t-SNE approach
E Pouyet, N Rohani, AK Katsaggelos, O Cossairt, M Walton
Pure and Applied Chemistry 90 (3), 493-506, 2018
Deep multi-view models for glitch classification
S Bahaadini, N Rohani, S Coughlin, M Zevin, V Kalogera, ...
2017 ieee international conference on acoustics, speech and signal …, 2017
Data quality up to the third observing run of advanced LIGO: Gravity Spy glitch classifications
J Glanzer, S Banagiri, SB Coughlin, S Soni, M Zevin, CPL Berry, O Patane, ...
Classical and Quantum Gravity 40 (6), 065004, 2023
Nonlinear unmixing of hyperspectral datasets for the study of painted works of art
N Rohani, E Pouyet, M Walton, O Cossairt, AK Katsaggelos
Angewandte Chemie 130 (34), 11076-11080, 2018
Direct: Deep discriminative embedding for clustering of ligo data
S Bahaadini, N Rohani, AK Katsaggelos, V Noroozi, S Coughlin, M Zevin
2018 25th ieee international conference on image processing (icip), 748-752, 2018
Knowledge tracing to model learning in online citizen science projects
K Crowston, C Řsterlund, TK Lee, C Jackson, M Harandi, S Allen, ...
IEEE Transactions on Learning Technologies 13 (1), 123-134, 2019
Automatic pigment identification on roman egyptian paintings by using sparse modeling of hyperspectral images
N Rohani, J Salvant, S Bahaadini, O Cossairt, M Walton, A Katsaggelos
2016 24th European signal processing conference (EUSIPCO), 2111-2115, 2016
Pigment unmixing of hyperspectral images of paintings using deep neural networks
N Rohani, E Pouyet, M Walton, O Cossairt, AK Katsaggelos
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
Teaching citizen scientists to categorize glitches using machine learning guided training
C Jackson, C Řsterlund, K Crowston, M Harandi, S Allen, S Bahaadini, ...
Computers in Human Behavior 105, 106198, 2020
Guess and determine attack on Trivium family
N Rohani, Z Noferesti, J Mohajeri, MR Aref
2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing …, 2010
Neural networks for modeling neural spiking in S1 cortex
A Lucas, T Tomlinson, N Rohani, R Chowdhury, SA Solla, ...
Frontiers in systems neuroscience 13, 13, 2019
Artificial intelligence for pigment classification task in the short-wave infrared range
E Pouyet, T Miteva, N Rohani, L de Viguerie
Sensors 21 (18), 6150, 2021
C sterlund, JR Smith, L Trouille, and V Kalogera. Gravity spy: integrating advanced ligo detector characterization, machine learning, and citizen science
M Zevin, S Coughlin, S Bahaadini, E Besler, N Rohani, S Allen, M Cabero, ...
Classical and Quantum Gravity 34 (6), 064003, 2017
Graph-based identification of boundary points for unmixing and anomaly detection
N Rohani, M Parente
2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in …, 2013
Gravity spy machine learning classifications of LIGO glitches from observing runs O1
J Glanzer, S Banagari, S Coughlin, M Zevin, S Bahaadini, N Rohani, ...
O2, O3a and O3b (v1. 0.0) Zenodo, 2021
Distinguishing Nigerian Food Items and Calorie Content with Hyperspectral Imaging
X Wang, N Rohani, A Manerikar, A Katsagellos, O Cossairt, N Alshurafa
New Trends in Image Analysis and Processing–ICIAP 2017: ICIAP International …, 2017
Variational gaussian process for sensor fusion
N Rohani, P Ruiz, E Besler, R Molina, AK Katsaggelos
2015 23rd European Signal Processing Conference (EUSIPCO), 170-174, 2015
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