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Sannasi Chakravarthy S R
Sannasi Chakravarthy S R
Unknown affiliation
Verified email at bitsathy.ac.in
Title
Cited by
Cited by
Year
Analysis of decision tree and k-nearest neighbor algorithm in the classification of breast cancer
H Rajaguru, SC SR
Asian Pacific journal of cancer prevention: APJCP 20 (12), 3777, 2019
982019
Automatic detection and classification of mammograms using improved extreme learning machine with deep learning
SRS Chakravarthy, H Rajaguru
Irbm 43 (1), 49-61, 2022
812022
Performance analysis and detection of micro calcification in digital mammograms using wavelet features
C Abirami, R Harikumar, SRS Chakravarthy
2016 International Conference on Wireless Communications, Signal Processing …, 2016
652016
Lung cancer detection using probabilistic neural network with modified crow-search algorithm
SC SR, H Rajaguru
Asian Pacific journal of cancer prevention: APJCP 20 (7), 2159, 2019
542019
Detection and classification of microcalcification from digital mammograms with firefly algorithm, extreme learning machine and non‐linear regression models: A comparison
SR Sannasi Chakravarthy, H Rajaguru
International Journal of Imaging Systems and Technology 30 (1), 126-146, 2020
512020
Multi-deep CNN based experimentations for early diagnosis of breast cancer
SR Sannasi Chakravarthy, N Bharanidharan, H Rajaguru
IETE Journal of Research 69 (10), 7326-7341, 2023
242023
A novel improved crow‐search algorithm to classify the severity in digital mammograms
SR Sannasi Chakravarthy, H Rajaguru
International Journal of Imaging Systems and Technology 31 (2), 921-954, 2021
212021
Deep learning-based metaheuristic weighted k-nearest neighbor algorithm for the severity classification of breast cancer
SRS Chakravarthy, N Bharanidharan, H Rajaguru
IRBM 44 (3), 100749, 2023
202023
Comparison analysis of linear discriminant analysis and cuckoo-search algorithm in the classification of breast cancer from digital mammograms
SC SR, H Rajaguru
Asian Pacific journal of cancer prevention: APJCP 20 (8), 2333, 2019
162019
Deep‐features with Bayesian optimized classifiers for the breast cancer diagnosis
SR Sannasi Chakravarthy, H Rajaguru
International Journal of Imaging Systems and Technology 31 (4), 1861-1881, 2021
132021
A systematic review on screening, examining and classification of breast cancer
SC SR, H Rajaguru
2021 Smart Technologies, Communication and Robotics (STCR), 1-4, 2021
132021
Multiclass Paddy Disease Detection Using Filter Based Feature Transformation Technique
N Bharanidharan, SRS Chakravarthy, H Rajaguru, VV Kumar, TR Mahesh, ...
IEEE Access, 2023
112023
Comparison of Leapfrog and single term Haar wavelet series method to solve the second order linear system with singular-A
S Karunanithi, S Chakravarthy, S Sekar
J. Math. Comput. Sci. 4 (4), 804-816, 2014
102014
A systematic review on machine learning algorithms used for forecasting lake‐water level fluctuations
SR Sannasi Chakravarthy, N Bharanidharan, H Rajaguru
Concurrency and Computation: Practice and Experience 34 (24), e7231, 2022
82022
SKMAT‐U‐Net architecture for breast mass segmentation
SR Sannasi Chakravarthy, H Rajaguru
International Journal of Imaging Systems and Technology 32 (6), 1880-1888, 2022
62022
Adaptive median filtering with modified BDND algorithm for the removal of high-density impulse and random noise
SS Chakravarthy, SA Subhasakthe
Int J Comput Sci Mob Comput 4, 202-7, 2015
62015
A Study on Second-Order Linear Singular Systems using Leapfrog Method
S Karunanithi, S Chakravarthy, S Sekar
International Journal of Scientific & Engineering Research 5 (8), 747-750, 2014
62014
Performance analysis of ensemble classifiers and a two-level classifier in the classification of severity in digital mammograms
SR Sannasi Chakravarthy, H Rajaguru
Soft Computing 26 (22), 12741-12760, 2022
52022
Ensemble-based weighted voting approach for the early diagnosis of diabetes mellitus
SR Sannasi Chakravarthy, H Rajaguru
Sustainable Communication Networks and Application: Proceedings of ICSCN …, 2022
52022
Automatic detection and classification of mammograms using improved extreme learning machine with deep learning. IRBM 43 (1), 49–61
SR Sannasi Chakravarthy, H Rajaguru
52022
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