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ORCIDS. Chandrakala 0001
Person information
- affiliation: SASTRA University, Intelligent Systems Group, Thanjavur, Tamil Nadu, India
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2020 – today
- 2024
[j22]S. Chandrakala
, Vishnika Veni S:
Denoising Convolutional Autoencoder Based Approach for Disordered Speech Recognition. Int. J. Artif. Intell. Tools 33(1): 2350058:1-2350058:14 (2024)- [j21]S. Chandrakala, Akhilandeswari Pidikiti, P. V. N. Sai Mahathi:
Spectro Temporal Fusion with CLSTM-Autoencoder based approach for Anomalous Sound Detection. Neural Process. Lett. 56(1): 39 (2024) - 2023
- [j20]S. Chandrakala, K. Deepak, G. Revathy:
Anomaly detection in surveillance videos: a thematic taxonomy of deep models, review and performance analysis. Artif. Intell. Rev. 56(4): 3319-3368 (2023) - [j19]S. Chandrakala:
Anomalous human activity detection in videos using Bag-of-Adapted-Models-based representation. Pattern Anal. Appl. 26(3): 1101-1112 (2023) - 2022
- [j18]S. Malini, S. Chandrakala:
Intelligibility assessment of impaired speech using Regularized self-representation based compact supervectors. Comput. Speech Lang. 74: 101355 (2022) - [j17]S. Chandrakala, K. Deepak, L. K. P. Vignesh:
Bag-of-Event-Models based embeddings for detecting anomalies in surveillance videos. Expert Syst. Appl. 190: 116168 (2022) - [j16]S. Chandrakala, P. Shalmiya, V. Srinivas, K. Deepak:
Object-centric and memory-guided network-based normality modeling for video anomaly detection. Signal Image Video Process. 16(7): 2001-2007 (2022) - [j15]S. Chandrakala, L. K. P. Vignesh:
V2AnomalyVec: Deep Discriminative Embeddings for Detecting Anomalous Activities in Surveillance Videos. IEEE Trans. Comput. Soc. Syst. 9(5): 1307-1316 (2022) - 2021
- [j14]Vishnika Veni S, S. Chandrakala:
Investigation of DNN-HMM and Lattice Free Maximum Mutual Information Approaches for Impaired Speech Recognition. IEEE Access 9: 168840-168849 (2021) - [j13]K. Deepak, G. Srivathsan, S. Roshan, S. Chandrakala:
Deep Multi-view Representation Learning for Video Anomaly Detection Using Spatiotemporal Autoencoders. Circuits Syst. Signal Process. 40(3): 1333-1349 (2021) - [j12]S. Chandrakala, V. Srinivas, K. Deepak:
Residual Spatiotemporal Autoencoder with Skip Connected and Memory Guided Network for Detecting Video Anomalies. Neural Process. Lett. 53(6): 4677-4692 (2021) - [j11]K. Deepak, S. Chandrakala, C. Krishna Mohan:
Residual spatiotemporal autoencoder for unsupervised video anomaly detection. Signal Image Video Process. 15(1): 215-222 (2021) - [j10]S. Chandrakala, Venkatraman M, Shreyas N, S. L. Jayalakshmi:
Multi-view representation for sound event recognition. Signal Image Video Process. 15(6): 1211-1219 (2021) - [j9]S. Chandrakala, S. Malini, S. L. Jayalakshmi:
Bag of Models Based Embeddings for Assessment of Neurological Disorders Using Speech Intelligibility. IEEE Trans. Emerg. Top. Comput. 9(3): 1265-1275 (2021) - [c6]Niveditha Sekar, S. Chandrakala, G. Prakash:
Analysis of Global Word Representations for Depression Detection. ISIC 2021: 136-148 - 2020
- [j8]K. Deepak, L. K. P. Vignesh, S. Chandrakala:
Autocorrelation of gradients based violence detection in surveillance videos. ICT Express 6(3): 155-159 (2020) - [j7]K. Deepak, Mohamed Yacin Sikkandar, S. Siddharth, S. Chandrakala:
A Similarity Based Representation for Identifying Healthcare Anomalous Activities. J. Medical Imaging Health Informatics 10(4): 787-794 (2020) - [j6]S. Chandrakala, S. L. Jayalakshmi:
Generative Model Driven Representation Learning in a Hybrid Framework for Environmental Audio Scene and Sound Event Recognition. IEEE Trans. Multim. 22(1): 3-14 (2020)
2010 – 2019
- 2019
- [j5]S. Chandrakala, S. L. Jayalakshmi:
Environmental Audio Scene and Sound Event Recognition for Autonomous Surveillance: A Survey and Comparative Studies. ACM Comput. Surv. 52(3): 63:1-63:34 (2019) - 2017
- [j4]A. Pravin Renold, S. Chandrakala:
MRL-SCSO: Multi-agent Reinforcement Learning-Based Self-Configuration and Self-Optimization Protocol for Unattended Wireless Sensor Networks. Wirel. Pers. Commun. 96(4): 5061-5079 (2017) - [j3]A. Pravin Renold, S. Chandrakala:
Erratum to: MRL-SCSO: Multi-agent Reinforcement Learning-Based Self-Configuration and Self-Optimization Protocol for Unattended Wireless Sensor Networks. Wirel. Pers. Commun. 96(4): 5081 (2017) - 2016
- [j2]A. Pravin Renold, S. Chandrakala:
Survey on state scheduling-based topology control in unattended wireless sensor networks. Comput. Electr. Eng. 56: 334-349 (2016) - 2010
- [j1]S. Chandrakala, C. Chandra Sekhar:
Classification of varying length multivariate time series using Gaussian mixture models and support vector machines. Int. J. Data Min. Model. Manag. 2(3): 268-287 (2010)
2000 – 2009
- 2009
- [c5]S. Chandrakala, C. Chandra Sekhar:
Model Based Clustering of Audio Clips Using Gaussian Mixture Models. ICAPR 2009: 47-50 - [c4]Shanmuganathan Chandrakala, Chellu Chandra Sekhar:
Combination of generative models and SVM based classifier for speech emotion recognition. IJCNN 2009: 497-502 - [c3]S. Chandrakala, C. Chandra Sekhar:
Classification of Multi-variate Varying Length Time Series Using Descriptive Statistical Features. PReMI 2009: 13-18 - 2008
- [c2]S. Chandrakala, C. Chandra Sekhar:
A density based method for multivariate time series clustering in kernel feature space. IJCNN 2008: 1885-1890 - 2007
- [c1]Sheetal Reddy Pamudurthy, S. Chandrakala, C. Chandra Sekhar:
Local Density Estimation based Clustering. IJCNN 2007: 1249-1254
Coauthor Index
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