32 publications with the keyword "parallelization"


#160: M. Poostchi, K. Palaniappan, F. Bunyak, M. Becchi, and G. Seetharaman

Efficient GPU implementation of the integral histogram

Lecture Notes in Computer Science (ACCV Workshop on Developer-Centered Computer Vision), Volume 7728, pgs. 266--278, 2012

parallelization, gpu, tracking, fmv, motion, features, dod

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#146: M. Poostchi, K. Palaniappan, F. Bunyak, M. Becchi, and G. Seetharaman

Realtime motion detection based on the spatio-temporal median filter using GPU integral histograms

8th Indian Conference on Computer Vision, Graphics and Image Processing, 2012

parallelization, gpu, tracking, fmv, motion, features, dod

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#150: L. Wang, C. Shen, G. Seetharaman, K. Palaniappan, and S. Bhattacharyya

Multidimensional dataflow graph modeling and mapping for efficient GPU implementation

IEEE Workshop Signal Processing Systems (SiPS), pgs. 300--305, 2012

parallelization, gpu, tracking, fmv, motion, features, dod

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#127: P. Bellens, K. Palaniappan, R. M. Badia, G. Seetharaman, and J. Labarta

Parallel implementation of the integral histogram

Lecture Notes in Computer Science (ACIVS), Volume 6915, pgs. 586--598, 2011

parallelization, gpu, tracking, fmv, motion, features, dod

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#128: K. Palaniappan, I. Ersoy, G. Seetharaman, S. Davis, P. Kumar, R. M. Rao, and R. Linderman

Parallel flux tensor analysis for efficient moving object detection

14th Int. Conf. Information Fusion, 2011

parallelization, wami, tracking, fmv, motion, dod

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#110: K. Palaniappan, I. Ersoy, G. Seetharaman, S. Davis, R. Rao, and R. Linderman

Multicore energy efficient flux tensor for video analysis

IEEE Workshop on Energy Efficient High-Performance Computing (EEHiPC), 2010

parallelization, wami, tracking, fmv, motion, dod

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#92: K. Palaniappan, F. Bunyak, S. Nath, and J. Goffeney

Parallel processing strategies for cell motility and shape analysis

High-Throughput Image Reconstruction and Analysis, Artech House Publishers, pgs. 39--85, 2009

parallelization, gpu, cell detection, cell segmentation, cell tracking, machine learning, biomedical

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#94: P. Kumar, K. Palaniappan, A. Mittal, and G. Seetharaman

Parallel blob extraction using the multi-core Cell processor

Lecture Notes in Computer Science (ACIVS), Volume 5807, pgs. 320--332, 2009

parallelization, tracking, fmv, motion, features, dod

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#93: S. Mehta, A. Misra, A. Singhal, P. Kumar, A. Mittal, and K. Palaniappan

Parallel implementation of video surveillance algorithms on GPU architectures using CUDA

17th IEEE Int. Conf. Advanced Computing and Communications (ADCOM), 2009

parallelization, gpu, tracking, fmv, motion, features, dod

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#90: B. Shen, W. Tao, J. Chern, R. Atlas, and K. Palaniappan

Scalability improvements in the NASA Goddard Multiscale Modeling Framework for tropical cyclone climate studies

Proc. 10th Int. Conf. for High-Performance Computing in ASIA-Pacific Region, 2009

visualization, parallelization, features, motion, cloud

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#76: S. Grauer-Gray, C. Kambhamettu, and K. Palaniappan

GPU implementation of belief propagation using CUDA for cloud tracking and reconstruction

5th IAPR Workshop on Pattern Recognition in Remote Sensing (ICPR), pgs. 1--4, 2008

parallelization, gpu, tracking, stereo, fmv, motion, features, cloud

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#67: C. R. Shyu, M. Klaric, G. J. Scott, A. S. Barb, C. H. Davis, and K. Palaniappan

GeoIRIS: Geospatial information retrieval and indexing system -- Content mining, semantics, modeling, and complex queries

IEEE Trans. Geoscience Remote Sensing, Volume 45, pgs. 839--852, 2007

gis, data mining, features, machine learning, parallelization, cbir

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#58: S. J. Julier, J. K. Uhlmann, J. Walters, R. Mittu, and K. Palaniappan

The challenge of scalable and distributed fusion of disparate sources of information

SPIE Proc. Multisensor, Multisource Information Fusion: Architectures, Algorithms and Applications, Volume 6242, pgs. Online, 2006

gis, fusion, parallelization, data mining, remote sensing

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#46: S.-H. Jee and K. Palaniappan

Performance of dynamically scheduling VLIW instructions

IEEE Int. Symp. System-on-Chip, pgs. 7--10, 2003

parallelization, dod

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#45: S. Sangappa, K. Palaniappan, and R. Tollerton

Benchmarking Java against C/C++ for interactive scientific visualization

Proc Joint ACM-ISCOPE Conf. Java Grande, pgs. 236, 2002

visualization, parallelization, big data

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#44: S.-H. Jee and K. Palaniappan

Compiler processor tradeoffs for DISVLIW architectures

IEEE Int. Symp. On Parallel Architectures, Algorithms, and Networks (ISPAN), pgs. 175--180, 2002

parallelization, dod

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#42: S.-H. Jee and K. Palaniappan

Performance analysis for a compressed-VLIW processor

ACM Symp. on Applied Computing, pgs. 913--917, 2002

parallelization, dod

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#43: S.-H. Jee and K. Palaniappan

Dynamically scheduling VLIW instructions with dependency information

8th IEEE Int. Symp. On High-Performance Computer Architecture and 6th Workshop on Interaction Between Compilers and Computer Architectures, pgs. 15--23, 2002

parallelization, dod

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#35: L. Zhou, C. Kambhamettu, D. Goldgof, K. Palaniappan, and A. F. Hasler

Tracking non-rigid motion and structure from 2D satellite cloud images without correspondences

IEEE Trans. Pattern Analysis and Machine Intelligence, Volume 23, pgs. 1330--1336, 2001

motion, tracking, parallelization, cloud, remote sensing

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#37: K. Palaniappan and J. Fraser

Multiresolution tiling for interactive viewing of large datasets

17th Int. AMS Conf. on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography and Hydrology, pgs. 338--342, 2001

visualization, big data, parallelization, cloud, remote sensing

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#36: K. Palaniappan, A. Hasler, J. Fraser, and M. Manyin

Network-based visualization using the distributed image spreadsheet (DISS)

17th Int. AMS Conf. on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography and Hydrology, pgs. 399--403, 2001

visualization, big data, parallelization, cloud, remote sensing

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#38: C. Kambhamettu, K. Palaniappan, and A. Hasler

Hierarchical motion decomposition for cloud-tracking

17th Int. AMS Conf. on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography and Hydrology, pgs. 318--323, 2001

motion, tracking, parallelization, cloud, remote sensing

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#24: A. F. Hasler, K. Palaniappan, C. Kambhamettu, P. Black, E. Uhlhorn, and D. Chesters

High resolution windfields within the inner core and eye of a mature tropical cyclone from GOES 1-min images

Bulletin of the American Meteorological Society, Volume 79, pgs. 2483--2496, 1998

motion, parallelization, visualization, cloud, big data, remote sensing

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#22: K. Palaniappan, J. Vass, and X. Zhuang

Parallel robust relaxation algorithm for automatic stereo analysis

SPIE Proc. Parallel and Distributed Methods for Image Processing II, Volume 3452, pgs. 958--962, 1998

parallelization, stereo, features

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#20: A. F. Hasler, P. Black, V. M. Karyampudi, M. Jentoft-Nilsen, K. Palaniappan, and D. Chesters

Synthesis of eyewall mesovortex and supercell convective structures in Hurricane Luis with GOES-8/9 stereo, concurrent 1-min GOES-9 and NOAA airborne radar observations

22nd AMS Conf. on Hurricanes and Tropical Meteorology, pgs. 201--202, 1997

motion, parallelization, stereo, cloud, big data, remote sensing

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#15: K. Palaniappan, M. Faisal, C. Kambhamettu, and A. F. Hasler

Implementation of an automatic semi-fluid motion analysis algorithm on a massively parallel computer

10th IEEE Int. Parallel Processing Symp., pgs. 864--872, 1996

motion, parallelization, stereo, cloud, big data, remote sensing

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#16: A. F. Hasler, D. Chesters, M. Jentoft-Nilsen, and K. Palaniappan

High performance animation of GOES weather images

SPIE Proc. on GOES-8 and Beyond, Volume 2812, pgs. 80--83, 1996

visualization, parallelization, stereo, cloud, big data, remote sensing

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#19: C. Kambhamettu, K. Palaniappan, and A. F. Hasler

Automated cloud-drift winds from GOES images

SPIE Proc. on GOES-8 and Beyond, Volume 2812, pgs. 122--133, 1996

motion, visualization, parallelization, stereo, cloud, big data, remote sensing

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#14: C. Kambhamettu, K. Palaniappan, and A. F. Hasler

Coupled, multi-resolution stereo and motion analysis

IEEE Int. Symp. Computer Vision, pgs. 43--48, 1995

motion, visualization, parallelization, stereo, cloud, big data, remote sensing

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#9: A. F. Hasler, K. Palaniappan, M. Manyin, and J. Dodge

A high performance interactive image spreadsheet (IISS)

Computers in Physics, Volume 8, pgs. 325--342, 1994

visualization, parallelization, image analysis, remote sensing

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#8: K. Palaniappan, A. Hasler, and M. Manyin

Exploratory analysis of satellite data using the Interactive Image Spreadsheet (IISS) environment

9th Int. AMS Conf. on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography and Hydrology, pgs. 145--152, 1993

visualization, parallelization, image analysis, remote sensing

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#7: A. Hasler, K. Palaniappan, and D. Chesters

Visualization of multispectral and multisource data using an interactive image spreadsheet (IISS)

8th Int. AMS Conf. on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography and Hydrology, pgs. 85--92, 1992

visualization, parallelization, image analysis, remote sensing

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