Ranga Raju Vatsavai

Also known as: Raju

https://orcid.org/0000-0002-7083-0267

Machine Learning, Data Mining, Spatial and Temporal, Remote Sensing, Image and Video Understanding, Computer Vision, Crop Biomass Monitoring, Settlement Mapping, HPC, Spatial Databases

Works (35)

2022 journal article

A Survey of Single-Scene Video Anomaly Detection

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 5.

By: B. Ramachandra, M. Jones & R. Vatsavai

Sources: Web Of Science, ORCID
Added: May 23, 2022

2021 article

A Scalable System for Searching Large-scale Multi-sensor Remote Sensing Image Collections

2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA).

By: Y. Zhao, X. Yang & R. Vatsavai

Sources: Web Of Science, ORCID
Added: July 5, 2022

2021 article

Local Clustering with Mean Teacher for Semi-supervised learning

2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR).

By: Z. Chen, B. Dutton, B. Ramachandra, T. Wu & R. Vatsavai

Sources: Web Of Science, ORCID
Added: August 30, 2021

2021 journal article

Perceptual metric learning for video anomaly detection

MACHINE VISION AND APPLICATIONS, 32(3).

By: B. Ramachandra, M. Jones & R. Vatsavai

Sources: Web Of Science, ORCID
Added: April 5, 2021

2019 journal article

Anomalous cluster detection in spatiotemporal meteorological fields

STATISTICAL ANALYSIS AND DATA MINING, 12(2), 88–100.

By: B. Ramachandra, B. Dutton & R. Vatsavai

Sources: Web Of Science, ORCID
Added: April 9, 2019

2018 article

Deformable Part Models for Complex Object Detection in Remote Sensing Imagery

BIGSPATIAL 2018: PROCEEDINGS OF THE 7TH ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON ANALYTICS FOR BIG GEOSPATIAL DATA (BIGSPATIAL-2018), pp. 57–62.

By: N. Pool & R. Vatsavai

Sources: Web Of Science, ORCID
Added: July 1, 2019

2018 article

FUTURES-DPE: Towards Dynamic Provisioning and Execution of Geosimulations in HPC environments

26TH ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS (ACM SIGSPATIAL GIS 2018), pp. 464–467.

By: A. Shashidharan, R. Vatsavai & R. Meentemeyer

Sources: Web Of Science, ORCID
Added: December 2, 2019

2018 article

Machine Learning Approaches for Slum Detection Using Very High Resolution Satellite Images

2018 18TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW), pp. 1397–1404.

By: K. Gadiraju, R. Vatsavai, N. Kaza, E. Wibbels & A. Krishna

Sources: Web Of Science, ORCID
Added: June 17, 2019

2018 journal article

Real-Time Energy Audit of Built Environments: Simultaneous Localization and Thermal Mapping

JOURNAL OF INFRASTRUCTURE SYSTEMS, 24(3).

By: B. Ramachandra, P. Nawathe, J. Monroe, K. Han, Y. Ham & R. Vatsavai

Sources: NC State University Libraries, ORCID
Added: October 19, 2018

2017 conference paper

Hierarchical change detection framework for biomass monitoring

2017 ieee international geoscience and remote sensing symposium (igarss), 620–623.

By: Z. Chen, B. Ramachandra & R. Vatsavai

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2017 journal article

High performance GPU computing based approaches for oil spill detection from multi-temporal remote sensing data

Remote Sensing of Environment, 202, 28–44.

By: U. Bhangale, S. Durbha, R. King, N. Younan & R. Vatsavai

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2017 conference paper

Parallel processing over spatial-temporal datasets from geo, bio, climate and social science communities: A research roadmap

2017 ieee 6th international congress on big data (bigdata congress 2017), 232–250.

By: S. Prasad, D. Aghajarian, M. McDermott, D. Shah, M. Mokbel, S. Puri, S. Rey, S. Shekhar ...

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2017 journal article

Semantics-enabled framework for spatial image information mining of linked earth observation data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(1), 29–44.

By: K. Kurte, S. Durbha, R. King, N. Younan & R. Vatsavai

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2017 conference paper

Semi-supervised deep generative models for change detection in very high resolution imagery

2017 ieee international geoscience and remote sensing symposium (igarss), 1063–1066.

By: C. Connors & R. Vatsavai

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2016 conference paper

A A scalable probabilistic change detection algorithm for very high resolution (VHR) satellite imagery

2016 ieee international congress on big data - bigdata congress 2016, 275–282.

By: S. Hong & R. Vatsavai

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2016 journal article

Detecting Extreme Events in Gridded Climate Data

Procedia Computer Science, 80, 2397–2401.

By: B. Ramachandra, K. Gadiraju, R. Vatsavai, D. Kaiser & T. Karnowski

Sources: Crossref, ORCID
Added: February 21, 2020

2016 journal article

Guest editorial: Big spatial data

Geoinformatica, 20(4), 797–799.

By: R. Vatsavai & V. Chandola

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2016 journal article

Mapping Magnetic Ordering With Aberrated Electron Probes in STEM

Microscopy and Microanalysis, 22(S3), 1676–1677.

By: J. Idrobo, J. Rusz, J. Spiegelberg, M. McGuire, C. Symons, R. Vatsavai, C. Cantoni, A. Lupini

Sources: Crossref, ORCID
Added: February 21, 2020

2016 journal article

Monitoring land-cover changes: A machine-learning perspective

IEEE Geoscience and Remote Sensing Magazine, 4(2), 8–21.

By: A. Karpatne, Z. Jiang, R. Vatsavai, S. Shekhar & V. Kumar

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2016 conference paper

Scalable nearest neighbor based hierarchical change detection framework for crop monitoring

2016 IEEE International Conference on Big Data (Big Data), 1309–1314.

By: Z. Chen, R. Vatsavai, B. Ramachandra, Q. Zhang, N. Singh & S. Sukumar

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2016 journal article

Sliding Window-based Probabilistic Change Detection for Remote-sensed Images

Procedia Computer Science, 80, 2348–2352.

By: S. Hong & R. Vatsavai

Sources: Crossref, ORCID
Added: February 21, 2020

2016 conference paper

pFUTURES: A parallel framework for cellular automaton based urban growth models

Geographic information science, (giscience 2016), 9927, 163–177.

By: A. Shashidharan, D. Berkel, R. Vatsavai & R. Meentemeyer

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2015 conference paper

A A scalable complex pattern mining framework for global settlement mapping

2015 IEEE International Congress on Big Data - BigData congress 2015, 514–521.

By: R. Vatsavai

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2015 conference paper

Multitemporal data mining: From biomass monitoring to nuclear proliferation detection

2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp).

By: R. Vatsavai

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2012 journal article

Probabilistic Change Detection Framework for Analyzing Settlement Dynamics Using Very High-resolution Satellite Imagery

Procedia Computer Science, 9, 907–916.

By: R. Vatsavai & J. Graesser

Sources: Crossref, ORCID
Added: September 10, 2020

2011 journal article

A hybrid classification scheme for mining multisource geospatial data

GeoInformatica, 15(1), 29–47.

By: R. Vatsavai & B. Bhaduri

Sources: Crossref, ORCID
Added: December 28, 2020

2011 journal article

A scalable gaussian process analysis algorithm for biomass monitoring

Statistical Analysis and Data Mining, 4(4), 430–445.

By: V. Chandola & R. Vatsavai

Sources: Crossref, ORCID
Added: September 10, 2020

2011 journal article

Data Mining in Earth System Science (DMESS 2011)

Procedia Computer Science, 4, 1450–1455.

By: F. Hoffman, J. Larson, R. Mills, B. Brooks, A. Ganguly, W. Hargrove, J. Huang, J. Kumar, R. Vatsavai

Sources: Crossref, ORCID
Added: September 10, 2020

2011 journal article

GX-Means: A model-based divide and merge algorithm for geospatial image clustering

Procedia Computer Science, 4, 186–195.

By: R. Vatsavai, C. Symons, V. Chandola & G. Jun

Sources: Crossref, ORCID
Added: September 10, 2020

2009 chapter

Incremental Clustering Algorithm for Earth Science Data Mining

In G. Allen, J. Nabrzyski, E. Seidel, G. D. van Albada, J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2009 (pp. 375–384).

By: R. Vatsavai

Ed(s): G. Allen, J. Nabrzyski, E. Seidel, G. van Albada, J. Dongarra & P. Sloot

Sources: Crossref, ORCID
Added: December 28, 2020

2008 chapter

A Learning Scheme for Recognizing Sub-classes from Model Trained on Aggregate Classes

In Lecture Notes in Computer Science (pp. 967–976).

By: R. Vatsavai, S. Shekhar & B. Bhaduri

Sources: Crossref, ORCID
Added: September 10, 2020

2007 journal article

An efficient spatial semi-supervised learning algorithm

International Journal of Parallel, Emergent and Distributed Systems, 22(6), 427–437.

By: R. Vatsavai, S. Shekhar & T. Burk

Sources: Crossref, ORCID
Added: September 10, 2020

2006 chapter

Improving DB2 Performance Expert – A Generic Analysis Framework

In Lecture Notes in Computer Science (pp. 1097–1101).

By: L. Mignet, J. Basak, M. Bhide, P. Roy, S. Roy, V. Sengar, R. Vatsavai, M. Reichert ...

Sources: Crossref, ORCID
Added: September 10, 2020

2006 chapter

UMN-MapServer: A High-Performance, Interoperable, and Open Source Web Mapping and Geo-spatial Analysis System

In Geographic Information Science (pp. 400–417).

By: R. Vatsavai, S. Shekhar, T. Burk & S. Lime

Sources: Crossref, ORCID
Added: September 10, 2020

2004 chapter

Comparing Exact and Approximate Spatial Auto-regression Model Solutions for Spatial Data Analysis

In Geographic Information Science (pp. 140–161).

By: B. Kazar, S. Shekhar, D. Lilja, R. Vatsavai & R. Pace

Sources: Crossref, ORCID
Added: September 10, 2020

Employment

2014 - present

North Carolina State University Raleigh, North Carolina, US
Associate Professor Computer Science

Education

1999 - 2008

University of Minnesota System Minneapolis, MN, US
Ph.D. Computer Science