Local Density Estimation based Clustering. - Sheetal Reddy Pamudurthy; S. Chandrakala 001; C. Chandra Sekhar (IJCNN, 2007)

A density based method for multivariate time series clustering in kernel feature space. - S. Chandrakala 001; C. Chandra Sekhar (IJCNN, 2008)

Model Based Clustering of Audio Clips Using Gaussian Mixture Models. - S. Chandrakala 001; C. Chandra Sekhar (ICAPR, 2009)

Combination of generative models and SVM based classifier for speech emotion recognition. - Shanmuganathan Chandrakala; Chellu Chandra Sekhar (IJCNN, 2009)

Classification of Multi-variate Varying Length Time Series Using Descriptive Statistical Features. - S. Chandrakala 001; C. Chandra Sekhar (PReMI, 2009)

Classification of varying length multivariate time series using Gaussian mixture models and support vector machines. - S. Chandrakala 001; C. Chandra Sekhar (Int. J. Data Min. Model. Manag., 2010)

Survey on state scheduling-based topology control in unattended wireless sensor networks. - A. Pravin Renold; S. Chandrakala 001 (Comput. Electr. Eng., 2016)

MRL-SCSO: Multi-agent Reinforcement Learning-Based Self-Configuration and Self-Optimization Protocol for Unattended Wireless Sensor Networks. - A. Pravin Renold; S. Chandrakala 001 (Wirel. Pers. Commun., 2017)

Erratum to: MRL-SCSO: Multi-agent Reinforcement Learning-Based Self-Configuration and Self-Optimization Protocol for Unattended Wireless Sensor Networks. - A. Pravin Renold; S. Chandrakala 001 (Wirel. Pers. Commun., 2017)

Environmental Audio Scene and Sound Event Recognition for Autonomous Surveillance: A Survey and Comparative Studies. - S. Chandrakala 001; S. L. Jayalakshmi (ACM Comput. Surv., 2019)

Autocorrelation of gradients based violence detection in surveillance videos. - K. Deepak; L. K. P. Vignesh; S. Chandrakala 001 (ICT Express, 2020)

A Similarity Based Representation for Identifying Healthcare Anomalous Activities. - K. Deepak; Mohamed Yacin Sikkandar; S. Siddharth; S. Chandrakala 001 (J. Medical Imaging Health Informatics, 2020)

Generative Model Driven Representation Learning in a Hybrid Framework for Environmental Audio Scene and Sound Event Recognition. - S. Chandrakala 001; S. L. Jayalakshmi (IEEE Trans. Multim., 2020)

Analysis of Global Word Representations for Depression Detection. - Niveditha Sekar; S. Chandrakala 001; G. Prakash (ISIC, 2021)

Investigation of DNN-HMM and Lattice Free Maximum Mutual Information Approaches for Impaired Speech Recognition. - Vishnika Veni S; S. Chandrakala 001 (IEEE Access, 2021)

Deep Multi-view Representation Learning for Video Anomaly Detection Using Spatiotemporal Autoencoders. - K. Deepak; G. Srivathsan; S. Roshan; S. Chandrakala 001 (Circuits Syst. Signal Process., 2021)

Residual Spatiotemporal Autoencoder with Skip Connected and Memory Guided Network for Detecting Video Anomalies. - S. Chandrakala 001; V. Srinivas; K. Deepak (Neural Process. Lett., 2021)

Multi-view representation for sound event recognition. - S. Chandrakala 001; Venkatraman M; Shreyas N; S. L. Jayalakshmi (Signal Image Video Process., 2021)

Residual spatiotemporal autoencoder for unsupervised video anomaly detection. - K. Deepak; S. Chandrakala 001; C. Krishna Mohan (Signal Image Video Process., 2021)

Bag of Models Based Embeddings for Assessment of Neurological Disorders Using Speech Intelligibility. - S. Chandrakala 001; S. Malini; S. L. Jayalakshmi (IEEE Trans. Emerg. Top. Comput., 2021)

Intelligibility assessment of impaired speech using Regularized self-representation based compact supervectors. - S. Malini; S. Chandrakala 001 (Comput. Speech Lang., 2022)

Bag-of-Event-Models based embeddings for detecting anomalies in surveillance videos. - S. Chandrakala 001; K. Deepak; L. K. P. Vignesh (Expert Syst. Appl., 2022)

Object-centric and memory-guided network-based normality modeling for video anomaly detection. - S. Chandrakala 001; P. Shalmiya; V. Srinivas; K. Deepak (Signal Image Video Process., 2022)

V2AnomalyVec: Deep Discriminative Embeddings for Detecting Anomalous Activities in Surveillance Videos. - S. Chandrakala 001; L. K. P. Vignesh (IEEE Trans. Comput. Soc. Syst., 2022)

Anomaly detection in surveillance videos: a thematic taxonomy of deep models, review and performance analysis. - S. Chandrakala 001; K. Deepak; G. Revathy (Artif. Intell. Rev., 2023)

Anomalous human activity detection in videos using Bag-of-Adapted-Models-based representation. - S. Chandrakala 001 (Pattern Anal. Appl., 2023)

Denoising Convolutional Autoencoder Based Approach for Disordered Speech Recognition. - S. Chandrakala 001; Vishnika Veni S (Int. J. Artif. Intell. Tools, 2024)

Spectro Temporal Fusion with CLSTM-Autoencoder based approach for Anomalous Sound Detection. - S. Chandrakala 001; Akhilandeswari Pidikiti; P. V. N. Sai Mahathi (Neural Process. Lett., 2024)