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Tirtharaj Dash
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A review of some techniques for inclusion of domain-knowledge into deep neural networks
T Dash, S Chitlangia, A Ahuja, A Srinivasan
Scientific Reports 12 (1), 1040, 2022
136*2022
A study on intrusion detection using neural networks trained with evolutionary algorithms
T Dash
Soft Computing 21 (10), 2687-2700, 2017
982017
Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network
RR Swain, PM Khilar, T Dash
Digital Communications and Networks 6 (1), 86-100, 2020
422020
A complete diagnosis of faulty sensor modules in a wireless sensor network
RR Swain, T Dash, PM Khilar
Ad Hoc Networks 93, 101924, 2019
312019
Hybrid gravitational search and particle swarm based fuzzy MLP for medical data classification
T Dash, SK Nayak, HS Behera
Computational Intelligence in Data Mining-Volume 1: Proceedings of the …, 2015
292015
Neural network based automated detection of link failures in wireless sensor networks and extension to a study on the detection of disjoint nodes
RR Swain, PM Khilar, T Dash
Journal of Ambient Intelligence and Humanized Computing 10, 593-610, 2019
282019
Large-scale assessment of deep relational machines
T Dash, A Srinivasan, L Vig, OI Orhobor, RD King
Inductive Logic Programming: 28th International Conference, ILP 2018 …, 2018
282018
Time efficient approach to offline hand written character recognition using associative memory net
T Dash
arXiv preprint arXiv:1306.4592, 2013
262013
An effective graph‐theoretic approach towards simultaneous detection of fault (s) and cut (s) in wireless sensor networks
RR Swain, T Dash, PM Khilar
International Journal of Communication Systems 30 (13), e3273, 2017
252017
Controlling wall following robot navigation based on gravitational search and feed forward neural network
T Dash, T Nayak, RR Swain
Proceedings of the 2nd international conference on perception and machine …, 2015
252015
Incorporating symbolic domain knowledge into graph neural networks
T Dash, A Srinivasan, L Vig
Machine Learning 110 (7), 1609-1636, 2021
232021
Fault diagnosis and its prediction in wireless sensor networks using regressional learning to achieve fault tolerance
RR Swain, PM Khilar, T Dash
International Journal of Communication Systems 31 (14), e3769, 2018
222018
Offline handwritten signature verification using Associative Memory Net
T Dash, T Nayak, S Chattopadhyay
International Journal of Advanced Research in Computer Engineering …, 2012
212012
Offline verification of hand written signature using adaptive resonance theory net (type-1)
T Dash, T Nayak, S Chattopadhyay
Proc: IEEE Int. Conf. Electronics Computer Technology (ICECT) 2, 205-210, 2012
212012
Transformational machine learning: Learning how to learn from many related scientific problems
I Olier, OI Orhobor, T Dash, AM Davis, LN Soldatova, J Vanschoren, ...
Proceedings of the National Academy of Sciences 118 (49), e2108013118, 2021
202021
Automatic navigation of wall following mobile robot using adaptive resonance theory of type-1
T Dash
Biologically Inspired Cognitive Architectures 12, 1-8, 2015
202015
English character recognition using artificial neural network
T Dash, T Nayak
arXiv preprint arXiv:1306.4621, 2013
202013
Gradient gravitational search: an efficient metaheuristic algorithm for global optimization
T Dash, PK Sahu
Journal of computational chemistry 36 (14), 1060-1068, 2015
192015
Performance evaluation of deep neural networks for forecasting time‐series with multiple structural breaks and high volatility
R Kaushik, S Jain, S Jain, T Dash
CAAI Transactions on Intelligence Technology 6 (3), 265-280, 2021
182021
Neural network approach to control wall-following robot navigation
T Dash, SR Sahu, T Nayak, G Mishra
2014 IEEE International Conference on Advanced Communications, Control and …, 2014
172014
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