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Tajunisha N
Tajunisha N
Professor, Sri Ramakrishna College of Arts & Science for women, Coimbatore.
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Cited by
Cited by
Year
Performance analysis of k-means with different initialization methods for high dimensional data
VSN Tajunisha
International Journal of Artificial Intelligence and Applications 1 (4), 44-52, 2010
352010
An efficient method to improve the clustering performance for high dimensional data by principal component analysis and modified K-means
N Tajunisha, V Saravanan
International Journal of Database Management Systems 3 (1), 196-205, 2011
192011
An increased performance of clustering high dimensional data using Principal Component Analysis
N Tajunisha, V Saravanan
2010 First International Conference on Integrated Intelligent Computing, 17-21, 2010
192010
A study on evolution of data analytics to big data analytics and its research scope
S Sruthika, N Tajunisha
2015 International Conference on Innovations in Information, Embedded and …, 2015
132015
Predicting Student Performance Using MapReduce
N Tajunisha, M Anjali
International journal of Emerging and Computer Science, ISSN: 2319-7242 4 …, 2015
122015
A new approach to improve the clustering accuracy using informative genes for unsupervised microarray data sets
N Tajunisha, V Saravanan
International Journal of Advanced Science and Technology 27, 85-94, 2011
102011
Classification of cancer datasets using artificial bee colony and deep feed forward neural networks
M Karunyalakshmi, N Tajunisha
International Journal of Advanced Research in Computer and Communication …, 2017
82017
Automatic classification of ovarian cancer types from CT images using deep semi-supervised generative learning and convolutional neural network
N Nagarajan, P.H., Tajunisha
Revue d'Intelligence Artificielle 35 (4), pp. 273–280, 2021
72021
Concept and Term Based Similarity Measure for Text Classification and Clustering
B Sindhiya, N Tajunisha
IJERST, ISSN-2319-5991 3 (1), 2014
72014
OPTIMAL PARAMETER SELECTION-BASED DEEP SEMI-SUPERVISED GENERATIVE LEARNING AND CNN FOR OVARIAN CANCER CLASSIFICATION.
PH Nagarajan, N Tajunisha
ICTACT Journal on Soft Computing 13 (2), 2023
42023
An improved method of unsupervised sample clustering based on information genes for microarray cancer data sets
N Tajunisha, V Saravanan
IJCB 2 (1), 2431, 2011
32011
Improved channel aware AOMDV routing protocol in manet
P Jeevajothi, N Tajunisha
International Journal of Computer Science and Management Research, ISSN 1 (4 …, 2012
22012
An increased performance of clustering high dimensional data using Priniciapl Component Analysis, 2010 First International Conference on Integrated Intelligent Computing
N Tajunisha, V Saravanan
DOI 10 (09), 2010
2*2010
An Improved DCNN Classification based on a Modified U-Net Segmentation Approach for Ovarian Cancer
N Nagarajan, P.H., Tajunisha
International Journal of Intelligent Engineering and Systems, 2022
12022
Automatic Classification of Ovarian Cancer Types from CT Images Using Deep Semi-Supervised Generative Learning and Convolutional Neural Network
N Nagarajan, P.H., Tajunisha
Revue d'Intelligence ArtificielleThis link is disabled. 35 (4), 273–280, 2021
2021
Ovarian component analysis: A novel ovarian cancer detection strategies using ovarian cancer classification models towards identifying the survival rate
N Nagarajan, P.H., Tajunisha
Journal of Advanced Research in Dynamical and Control Systems, 2020
2020
MR-CFRVM-ACO with Feature Selection for Efficient Data Mining by Monotonic Constraints
DNT A. Shanmugapriya
Journal of Adv Research in Dynamical & Control Systems 11 (07-Special Issue), 2019
2019
Analysis of Dengue Infection Prognosis Using Classification Techniques
DNT Griizma K.R
International Journal of Research and Analytical Reviews 6 (1), 2019
2019
A Hybrid Fuzzy C-Means Clustering with Artificial Fish Swarm Algorithm Optimization for Data Mining with Cascade RMC-FSVM
A Shanmugapriya, N Tajunisha
Fuzzy Systems, 57-63, 2018
2018
A Survey on Ovarian Cancer Detection using Data Mining Techniques
DNT Pillai Honey Nagarajan
International Journal of Theoretical and Applied Sciences 10 (1), 2018
2018
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