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madasamy sornam
madasamy sornam
在 unom.ac.in 的电子邮件经过验证
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引用次数
引用次数
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A survey on image classification and activity recognition using deep convolutional neural network architecture
M Sornam, K Muthusubash, V Vanitha
2017 ninth international conference on advanced computing (ICoAC), 121-126, 2017
582017
A new linear adaptive swarm intelligence approach using back propagation neural network for dental caries classification
M Sornam, M Prabhakaran
2017 IEEE International Conference on Power, Control, Signals and …, 2017
282017
Segmentation and classification of brain tumor using wavelet and Zernike based features on MRI
M Sornam, MS Kavitha, R Shalini
2016 IEEE International Conference on Advances in Computer Applications …, 2016
252016
Logit-based artificial bee colony optimization (LB-ABC) approach for dental caries classification using a back propagation neural network
M Sornam, M Prabhakaran
Integrated intelligent computing, communication and security, 79-91, 2019
212019
Deep convolutional neural network for handwritten tamil character recognition using principal component analysis
M Sornam, C Vishnu Priya
Smart and Innovative Trends in Next Generation Computing Technologies: Third …, 2018
152018
Classification of ancient handwritten Tamil characters on palm leaf inscription using modified adaptive backpropagation neural network with GLCM features
PM Devi, M Sornam
ACM Transactions on Asian and Low-Resource Language Information Processing …, 2020
82020
Hysteresis thresholding based edge detectors for inscriptional image enhancement
M Sornam, MS Kavitha, M Nivetha
2016 IEEE International Conference on Computational Intelligence and …, 2016
72016
Intermittent Leather Defect Detection Based on Ensemble Algorithms Derived from Black Hat Transformation and Hough Transformation
SN Vasagam, M Sornam
ICT Analysis and Applications, 35-45, 2022
52022
Application of chebyshev neural network for function approximation
M Sornam, V Vanitha
International Journal of Computer Sciences and Engineering 6 (4), 201-204, 2018
52018
An efficient morlet function based adaptive method for faster backpropagation for handwritten character recognition
M Sornam, MS Kavitha, MP Devi
2016 IEEE International Conference on Advances in Computer Applications …, 2016
52016
Deep convolutional networks in gender classification using dental X-ray images
L Nithya, M Sornam
Artificial Intelligence and Evolutionary Computations in Engineering Systems …, 2022
42022
The discovery of normality of body weight using principal component analysis: a comparative study on machine learning techniques using different data pre-processing methods
M Sornam, M Meharunnisa
International Journal of Knowledge Engineering and Data Mining 6 (1), 74-88, 2019
42019
Noise Removal using Chebyshev Functional Link Artificial Neural Network with Back propagation.
M Sornam, V Vanitha, TG Ashmitha
International Journal of Advanced Research in Computer Science 8 (5), 2017
42017
Oil spill and look-alike spots from SAR imagery using otsu method and artificial neural network
M Sornam
Int. J. Eng. Technol. Manag. Res 4, 1-10, 2017
42017
Species Wise Classification of Crust Leather images based on histogram equalization
SN Vasagam, M Sornam
2022 6th International Conference on Computing Methodologies and …, 2022
32022
Artificial Intelligence in Orthodontics-An exposition
M Sornam
2022 6th International Conference on Computing Methodologies and …, 2022
32022
Tamil Palm Leaf Manuscript Character Segmentation using GLCM feature extraction
PDM M. Sornam
Intl. Journal of Computer Science and Engineering 6 (4), 2018
32018
A revolutionary approach to cloud computing, security and its user compliance
MR Sudha, M Sornam
Indian Journal of Science and Technology 10 (1), 1-8, 2017
32017
A survey on back propagation neural network
M Sornam, MP Devi
International Journal of Communication and Networking System 5 (1), 70-74, 2016
32016
Tomato Disease Detection Using Convolutional Neural Network and Fuzzy Logic
L Vijayalakshmi, M Sornam
Artificial Intelligence and Evolutionary Computations in Engineering Systems …, 2022
22022
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