| 2009 | ||
|---|---|---|
| 21 | S. Chandrakala, C. Chandra Sekhar: Classification of Multi-variate Varying Length Time Series Using Descriptive Statistical Features. PReMI 2009: 13-18 | |
| 20 | Ved Prakash Sahu, Harendra Kumar Mishra, C. Chandra Sekhar: Variational Bayes Adapted GMM Based Models for Audio Clip Classification. PReMI 2009: 513-518 | |
| 2008 | ||
| 19 | A. Vijaya Rama Raju, C. Chandra Sekhar: An SVM Based Approach to Cross-Language Adaptation for Indian Languages. ICONIP (2) 2008: 394-401 | |
| 18 | B. Venkataramana B. Kini, C. Chandra Sekhar: Large margin AR model for time series classification. ICPR 2008: 1-4 | |
| 17 | S. Chandrakala, C. Chandra Sekhar: A density based method for multivariate time series clustering in kernel feature space. IJCNN 2008: 1885-1890 | |
| 16 | G. Haranadh, C. Chandra Sekhar: Hyperparameters of Gaussian process as features for trajectory classification. IJCNN 2008: 2195-2199 | |
| 2007 | ||
| 15 | Lakshmi Narayana Panuku, C. Chandra Sekhar: Clustering of Nonlinearly Separable Data Using Spiking Neural Networks. ICANN (1) 2007: 390-399 | |
| 14 | H. Swethalakshmi, C. Chandra Sekhar, V. Srinivasa Chakravarthy: Spatiostructural Features for Recognition of Online Handwritten Characters in Devanagari and Tamil Scripts. ICANN (2) 2007: 230-239 | |
| 13 | Venkataramana B. Kini, C. Chandra Sekhar: Kernel Auto-Regressive Model with eXogenous Inputs for Nonlinear Time Series Prediction. ICCTA 2007: 355-360 | |
| 12 | Lakshmi Narayana Panuku, C. Chandra Sekhar: Region-Based Encoding Method Using Multi-dimensional Gaussians for Networks of Spiking Neurons. ICONIP (1) 2007: 73-82 | |
| 11 | Venkataramana B. Kini, C. Chandra Sekhar: Multi-Scale Kernel Latent Variable Models for Nonlinear Time Series Pattern Matching. ICONIP (2) 2007: 11-20 | |
| 10 | Sheetal Reddy Pamudurthy, S. Chandrakala, C. Chandra Sekhar: Local Density Estimation based Clustering. IJCNN 2007: 1249-1254 | |
| 9 | R. Anitha, C. Chandra Sekhar: Acoustic Modeling using Vector Quantization in Kernel Feature Space and Classification using String Kernel based Support Vector Machines. IJCNN 2007: 1512-1517 | |
| 8 | R. Anitha, C. Chandra Sekhar: Acoustic Modeling Using Continuous Density Hidden Markov Models in the Mercer Kernel Feature Space. ISNN (1) 2007: 546-552 | |
| 2006 | ||
| 7 | D. Srikrishna Satish, C. Chandra Sekhar: Kernel based Clustering and Vector Quantization for Speech Segmentation. IJCNN 2006: 1636-1641 | |
| 6 | A. D. Dileep, C. Chandra Sekhar: Identification of Block Ciphers using Support Vector Machines. IJCNN 2006: 2696-2701 | |
| 2005 | ||
| 5 | Suryakanth V. Gangashetty, C. Chandra Sekhar, B. Yegnanarayana: Spotting Multilingual Consonant-Vowel Units of Speech Using Neural Network Models. NOLISP 2005: 303-317 | |
| 2004 | ||
| 4 | D. Srikrishna Satish, C. Chandra Sekhar: Kernel Based Clustering for Multiclass Data. ICONIP 2004: 1266-1272 | |
| 3 | R. Suguna, N. Sudha, C. Chandra Sekhar: A Fast and Efficient Face Detection Technique Using Support Vector Machine. ICONIP 2004: 338-343 | |
| 2002 | ||
| 2 | C. Chandra Sekhar, B. Yegnanarayana: A constraint satisfaction model for recognition of stop consonant-vowel (SCV) utterances. IEEE Transactions on Speech and Audio Processing 10(7): 472-480 (2002) | |
| 1998 | ||
| 1 | Ansgar Drolshagen, Walter Anheier, C. Chandra Sekhar: A Residue Number Arithmetic based Circuit for Pipelined Computation of Autocorrelation Coefficients of Speech Signal. VLSI Design 1998: 122-127 | |