Tirtharaj Dash
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A study on intrusion detection using neural networks trained with evolutionary algorithms
T Dash
Soft Computing 21 (10), 2687-2700, 2017
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
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
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
A complete diagnosis of faulty sensor modules in a wireless sensor network
RR Swain, T Dash, PM Khilar
Ad Hoc Networks 93, 101924, 2019
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
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
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
Time efficient approach to offline hand written character recognition using associative memory net
T Dash
arXiv preprint arXiv:1306.4592, 2013
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
Offline handwritten signature verification using Associative Memory Net
T Dash, T Nayak, S Chattopadhyay
International Journal of Advanced Research in Computer Engineering …, 2012
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
Incorporating symbolic domain knowledge into graph neural networks
T Dash, A Srinivasan, L Vig
Machine Learning 110 (7), 1609-1636, 2021
English character recognition using artificial neural network
T Dash, T Nayak
arXiv preprint arXiv:1306.4621, 2013
Gradient gravitational search: an efficient metaheuristic algorithm for global optimization
T Dash, PK Sahu
Journal of computational chemistry 36 (14), 1060-1068, 2015
Automatic navigation of wall following mobile robot using adaptive resonance theory of type-1
T Dash
Biologically Inspired Cognitive Architectures 12, 1-8, 2015
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
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
Incorporating domain knowledge into deep neural networks
T Dash, S Chitlangia, A Ahuja, A Srinivasan
arXiv preprint arXiv:2103.00180, 2021
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
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