Rohitash Chandra 个人学术档案

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引用	3152	2365
h 指数	29	26
i10 指数	74	50

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Mengjie Zhang，FRSNZ, FEngNZ, FIE...Professor of Computer Science, Victoria University of Wellington在 ecs.vuw.ac.nz 的电子邮件经过验证
Ehsan FarahbakhshEarthByte Group, School of Geosciences, University of Sydney在 sydney.edu.au 的电子邮件经过验证
Dietmar MüllerProfessor of Geophysics, EarthByte Group, Univ. of Sydney在 sydney.edu.au 的电子邮件经过验证
Marcus FreanVictoria University of Wellington在 ecs.vuw.ac.nz 的电子邮件经过验证
Sally (Wood) CrippsUniversity of Technology Sydney在 uts.edu.au 的电子邮件经过验证
Luc RollandAvailable for consultancy在 uws.ac.uk 的电子邮件经过验证
Christian OmlinUniversity of Agder, Norway在 uia.no 的电子邮件经过验证
Ratneel DeoGraduate Computer Scientist在 usp.ac.fj 的电子邮件经过验证
Yew-Soon OngPresident Chair Professor of Computer Science, A*Star AI Chief Scientist, FIEEE在 ntu.edu.sg 的电子邮件经过验证
Richard ScalzoCSIRO在 data61.csiro.au 的电子邮件经过验证
Hojat ShirmardPhD Candidate at the University of Sydney在 ut.ac.ir 的电子邮件经过验证
Hugo OlierookSenior Research Fellow in Geology, Curtin University在 curtin.edu.au 的电子邮件经过验证
Arpit KapoorPhD Candidate, UNSW Sydney在 unsw.edu.au 的电子邮件经过验证
Dr. Anuraganand SharmaThe University of the South Pacific, Fiji and University of Canberra, Australia在 usp.ac.fj 的电子邮件经过验证
Tristan SallesSchool of Geosciences, The University of Sydney在 sydney.edu.au 的电子邮件经过验证
Danial AzamUniversity of Sydney在 sydney.edu.au 的电子邮件经过验证
Abhishek GuptaRamanujan Faculty Fellow, IIT Goa; (formerly Scientist at A*STAR and NTU Singapore)在 iitgoa.ac.in 的电子邮件经过验证
Steven ReddyProfessor of Geology, Curtin University在 curtin.edu.au 的电子邮件经过验证
Chris ClarkProfessor of Geology, Curtin University在 curtin.edu.au 的电子邮件经过验证
Kavitesh Kumar BaliCentre for Frontier AI Research (CFAR), A*STAR, Singapore在 cfar.a-star.edu.sg 的电子邮件经过验证

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Rohitash Chandra

UNSW

在 unsw.edu.au 的电子邮件经过验证 - 首页

Bayesian deep learning Neuroevolution MCMC NLP Mineral Exploration


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Cooperative coevolution of Elman recurrent neural networks for chaotic time series prediction R Chandra, M Zhang Neurocomputing 86, 116-123, 2012	273	2012
Competition and Collaboration in Cooperative Coevolution of Elman Recurrent Neural Networks for Time-Series Prediction R Chandra IEEE Transactions on Neural Networks and Learning Systems, 2015	179	2015
A review of machine learning in processing remote sensing data for mineral exploration H Shirmard, E Farahbakhsh, D Muller, R Chandra Remote Sensing of Environment 268, 112750, 2022	163	2022
Evaluation of deep learning models for multi-step ahead time series prediction R Chandra, S Goyal, R Gupta IEEE Access 9, 83105-83123, 2021	155	2021
Deep learning via LSTM models for COVID-19 infection forecasting in India R Chandra, A Jain, DS Chauhan PLOS One 17 (1), e0262708, 2022	148	2022
COVID-19 sentiment analysis via deep learning during the rise of novel cases R Chandra, A Krishna PloS One 16 (8), e0255615, 2021	111	2021
Co-evolutionary multi-task learning with predictive recurrence for multi-step chaotic time series prediction R Chandra, YS Ong, CK Goh Neurocomputing 243, 21-34, 2017	91	2017
Evolutionary bagging for ensemble learning G Ngo, R Beard, R Chandra Neurocomputing, 2022	65	2022
Evaluation of co-evolutionary neural network architectures for time series prediction with mobile application in finance R Chandra, S Chand Applied Soft Computing 49, 462-473, 2016	58	2016
Computer vision-based framework for extracting geological lineaments from optical remote sensing data E Farahbakhsh, R Chandra, HKH Olierook, R Scalzo, C Clark, SM Reddy, ... International Journal of Remote Sensing, 2020	57	2020
A comparative study of convolutional neural networks and conventional machine learning models for lithological mapping using remote sensing data H Shirmard, E Farahbakhsh, E Heidari, A Beiranvand Pour, B Pradhan, ... Remote Sensing 14 (4), 819, 2022	55	2022
Integration of selective dimensionality reduction techniques for mineral exploration using ASTER satellite data H Shirmard, E Farahbakhsh, A Beiranvand Pour, AM Muslim, RD Müller, ... Remote Sensing 12 (8), 1261, 2020	55	2020
SMOTified-GAN for class imbalanced pattern classification problems A Sharma, PK Singh, R Chandra IEEE Access, 2022	52	2022
Co-evolutionary multi-task learning for dynamic time series prediction R Chandra, YS Ong, CK Goh Applied Soft Computing 70, 576-589, 2018	51	2018
Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic R Chandra, Y He PloS One 16 (7), e0253217, 2021	48	2021
Evolutionary multi-task learning for modular knowledge representation in neural networks R Chandra, A Gupta, YS Ong, CK Goh Neural Processing Letters 47 (3), 993-1009, 2018	48	2018
Evolutionary multi-task learning for modular training of feedforward neural networks R Chandra, A Gupta, YS Ong, CK Goh Neural Information Processing: 23rd International Conference, ICONIP 2016 …, 2016	48	2016
Bayesian geological and geophysical data fusion for the construction and uncertainty quantification of 3D geological models HKH Olierook, R Scalzo, D Kohn, R Chandra, E Farahbakhsh, ... Geoscience Frontiers, 2021	47	2021
Deep learning for predicting respiratory rate from biosignals AK Kumar, M Ritam, L Han, S Guo, R Chandra Computers in biology and medicine 144, 105338, 2022	45	2022
Design of a mobile face recognition system for visually impaired persons S Chaudhry, R Chandra arXiv preprint arXiv:1502.00756, 2015	45	2015

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