Recent Publications
Ghebrechristos, H., Alaghband, G. Immunizing Image Classifiers Against
Localized Adversary Attack, International Journal of Artificial Intelligence
& Applications (IJAIA), Vol. 15, No. 2, pp. 77-99
Linck, I., Gσmez, A.T. & Alaghband, G. "SVG-CNN: A shallow CNN based
on VGGNet applied to intra prediction partition block in HEVC". Multimed Tools
Appl (2024).
Ghebrechristos, H., Alaghband, G. 3D convolution for Proactive Defense
Against Localized Adversary Attacks, 12th International Conference on Soft
Computing, Artificial Intelligence and Applications (SCAI 2023), December 23, Sydney, Australia,
McCarthy, S., Alaghband, G., The Emotion Magnitude Effect: Navigating
Market Dynamics Amidst Supply Chain Events, J. Risk Financial Manag. 2023,
16(12), 490, (21 pages); https://doi.org/10.3390/jrfm16120490
Manh Huynh, Alaghband, G.," Multi-modal Sensor Framework with Learnable
Uncertainty Estimator for Pedestrian Trajectory Prediction, 2023 IEEE
Conference on Intelligent Transportation Systems (ITSC 2023).
Alghamdi,
T.; Alaghband, G. SAFEPA: An Expandable Multi-Pose Facial Expressions Pain
Assessment Method, Appl. Sci. 2023, 13, 7206.
McCarthy, S., Alaghband, G., Enhancing Financial Market Analysis and Prediction with Emotion Corpora and News Co-Occurrence Network, J. Risk Financial Manag. 2023, 16(4), 226.
Henok Ghebrechristos1*, Stence Nicholas2*, David Mirsky MD*, Manh Huynh,
Zackary Kromer, Ligia Batista1, Gita Alaghband PhD1, Brent ONeill MD2, Steven
Moulton MD, Daniel M. Lindberg MD, Deep Learning Mixture-of-Experts for Cytotoxic
Edema Assessment in Infants and Children, 2023 IEEE 20th International
Symposium on Biomedical Imaging (ISBI), Cartagena de Indias, Colombia
Ligia Batista*, Nicholas V. Stence, David M Mirsky, Terri Lewis, Sarah
Graber, Henok Ghebechristos, Gita Alaghband, Brent ONeil, Daniel M. Lindberg.,
Cytotoxic Edema is Associated with Injury Severity but not Abusive Mechanism
in Young Children with Severe Brain Injury, Annual Meeting of the Helfer
Society. April, 2023. Tucson, AZ.
Linck, I., Gomez, A. T., Alaghband, G. ," CNN Quadtree Depth Decision Prediction for Block Partitioning in HEVC Intra-Mode" 2023 Data Compression Conference (DCC 23), UT.
Manh Huynh, Alaghband, G.,"Online Adaptive Temporal Memory with Certainty Estimation for Human Trajectory Prediction," (WACV 23)
Alghamdi, T., Alaghband, G., Facial Expressions Based Automatic Pain Assessment System, Special Issue Recent Advances in Deep Learning for Image Analysis, Appl. Sci. 2022, 12(13), 6423; (16 pages) https://doi.org/10.3390/app12136423
Manh Huynh, Alaghband, G., "GPRAR: Graph Convolutional Network
based Pose Reconstruction and Action Recognition for Human Trajectory
Prediction," (2021).
Takano,
N., Alaghband,
G., Generator
From Edges: Reconstruction of Facial Images, 15th International
Symposium on Visual Computing (ISVC'20)
Manh, H., Alaghband,
G., AOL: Adaptive Online Learning for Human Trajectory Prediction in Dynamic
Video
Scenes,
The
British Machine Vision Conference (BMVC 20)
Ghebrechristos, H.,
Alaghband, G. Deep curriculum learning optimization. SN COMPUT. SCI. 1,
245 (2020). https://doi.org/10.1007/s42979-020-00251-7
Alghamdi, T., Alaghband,
G., A Novel CC*CNN Model for Face Recognition using Edge, 14th International Conference on Information
Technology and Applications (ICITA 2020), IRC Best
Paper Award.
Ghebrechristos, H.E, Alaghband,
G., Information Theory-Based Curriculum Learning Factory to Optimize Training, ACPR 2019. Lecture Notes in Computer Science, vol. 12046.
Springer, https://doi.org/10.1007/978-3-030-41404-7_29, Auckland, New Zealand.
Ghebrechristos, H.E, Alaghband,
G., Optimizing Training using Information Theory-Based Curriculum Learning
Factory, 31st
International Conference on Tools with Artificial Intelligence (ICTAI
2019).
Alghamdi, T., Alaghband,
G., High Performance Parallel Sort for Shared and Distributed Memory MIMD,
16th
International Conference in Applied Computing (AC2019), Cagliari, Italy.
Manh, H., Alaghband,
G., Trajectory Prediction by Coupling Scene-LSTM with Human Movement LSTM,
In:
Bebis G. et al. (eds) Advances in Visual Computing. ISVC 2019. Lecture
Notes in Computer Science, vol 11844, Springer. https://doi.org/10.1007/978-3-030-33720-9_19,
Lake Tahoe, Nevada
Manh, H., Alaghband,
G., Scene-LSTM: A Model for Human Trajectory Prediction, arXiv:1808.04018 [cs.CV], April 2019.
Takano, N., Alaghband, G., SRGAN: What the neural
network learns, The 23rd International Conference on Image
Processing, Computer Vision,& Pattern Recognition (IPCV'19) .
Ghebrechristos, H.E, Alaghband,
G., Expediting Training Using Information Theory-Based Patch Ordering
Algorithm, International Conference on Computational Science and
Computational Intelligence (CSCI'18).
Linck, I., Alaghband,
G., Test Zonal Search based on Region Label (TZSR) for Motion Estimation in
HEVC, (MMSP 2018) 2018 IEEE 20th International Workshop on Multimedia
Signal Processing, Vancouver, BC, 2018, pp. 1-6, doi: 10.1109/MMSP.2018.8547127.
Manh, H., Alaghband,
G., Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking,
Proceedings of the 15th Computer and Robot Vision (CRV 2018),
Toronto, Ontario, CA. doi:
10.1109/CRV.2018.00030
Gnabasik, D.,
Alaghband, G., A Data-driven Biomarker Computational Model for Lung Disease
Classification, Proceedings of the 10th International Conference on
Bioinformatics and Computational Biology (BICOB 2018), Las Vegas, USA.
Ghebrechristos, H.E, Alaghband,
G., RetiNet - Feature Extractor for Learning
Patterns of Diabetic Retinopathy and Age-Related Macular Degeneration from
Publicly Available Datasets, Health Informatics and Medical Systems
(CSCI-ISHI) in International Conference on Computational Science and
Computational Intelligence (CSCI'17), Las Vegas, USA.
Simonton, T., Alaghband,
G., Efficient and Accurate Word2Vec Implementations in GPU and Shared-Memory
Multicore Architectures, 2017 IEEE High Performance Extreme Computing
Conference (HPEC 17), Waltham, MA USA, 12
- 14 September 2017, pp. 1-7. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8091076
Alaghband, G., Fardi,
H. Z., Parallel Programming Multi-core Computers, Proceedings of the
2016 STEM Education Hawaii University International Conferences on Science, http://www.huichawaii.org/steam2016.html
, Honolulu, Hawaii, June 10-12, 2016 pp.1-11. http://www.huichawaii.org/assets/alaghband%2c-gita---2016-steam-huic.pdf
Vu, L., Alaghband, G., A Load Balancing Parallel Method for
Frequent Pattern Mining on Multi-core Cluster, Proceedings of HPC
Symposium, 2015 Spring Simulation Multi-Conference (SpringSim15), Simulation
Series, pp. 49-59, in Vol. 47, No.
4, April 12-15, 2015, Alexandria, Virginia, USA.
Vu, L., Alaghband, G., A Self-Adaptive Method for Frequent
Pattern Mining using a CPU-GPU Hybrid Model, Proceedings of HPC Symposium,
2015 Spring Simulation Multi-Conference (SpringSim15), Simulation Series,
pp. 192-202 in Vol. 47, No. 4, April 12-15, 2015, Alexandria, Virginia, USA.
Vu, L., Alaghband, G., Novel parallel method for
association rule mining on multi-core shared memory systems, Parallel Computing,
Volume 40, Issue 10, December 2014, Pages 768785. (Special Section on 2013
Workshop on Data Intensive Scalable Computing Systems (DISCS-2013) edited by
Dr. Philip C. Roth and Dr. Yong Chen, doi:10.1016/j.parco.2014.08.003, http://www.sciencedirect.com/science/article/pii/S0167819114001124
Vu, L., Alaghband, G., Efficient Algorithms for Mining Frequent Patterns from
Sparse and Dense Databases, Journal of Intelligent Systems, ISSN
(Online ahead of print) 2191-026X, ISSN (Print) 0334-1860, DOI: 10.1515/jisys-2014-0040,
September 2014, pp.181-197 in Vol. 24, Issue 2, March/April 2015.
Kern, D., and Alaghband, G., Parallel Processing of
Irregular Workloads on the GPGPU: Adaptive Quadrature, Proceedings of the PDPTA'14:
The 2014 International Conference on Parallel and Distributed Processing
Techniques and Applications, Vol. 2, pp. 423-429, July
21-24, 2014, Las Vegas, Nevada, USA, http://worldcomp-proceedings.com/proc/proc2014/pdpta.html,
http://worldcomp-proceedings.com/proc/p2014/PDP.htmlpp.
Fardi, H., Pace,
S., Alaghband, G., A Semiconductor Device Simulator Utilizing MATLAB, Proceedings
of the 2014 Hawaii University International Conferences on Science, Technology,
Engineering, Math and Education, http://www.huichawaii.org/steam2014p.html
, Honolulu, Hawaii, June 16-18, 2014 pp1-10. http://www.huichawaii.org/assets/fardi_hamid_-_et_al_stem_2014.pdf
Fardi, H.,
Alaghband, G., Assessment Strategies for Student Recruitment and Retention in
Engineering, Global Science and Technology Forum (GSTF), Journal on
Education (JED), Vol. 2, No. 1. pp. 74-80, June 2014. dl6.globalstf.org/index.php/jed/article/download/686/693
Gnabasik, D.,
Alaghband, G., Discrete Time Evolution of Proteomic Biomarkers, Proceedings
of the CSCI 2014, International Conference on Computational Science and
Computational Intelligence, Las Vegas, Nevada, USA, Vol. 2, pp. 11-16,
March 10-13, 2014. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6820887 , http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6822296
Vu, L., Alaghband, G. An Efficient
Approach for Mining Association Rules from Sparse and Dense Databases Proceedings
of the International Conference on
Information and Knowledge Management 2014
(ICIKM2014), World Congress on Computer and Information Systems 2014 (WCCAIS2014),
January 17-19, pp. 1-8, Hammamet, Tunisia. 10.1109/WCCAIS.2014.6916550, http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&tp=&arnumber=6916550
Vu, L.;
Alaghband, G., "Novel Parallel Method for Mining Frequent Patterns on
Multi-core Shared Memory Systems," in Proc. of the ACM 2013 Int. Workshop
on Data-Intensive Scalable Computing Systems, Supercomputing 2013, Nov
2013, pp. 49-54, Denver, Colorado. http://dl.acm.org/citation.cfm?id=2534653
Aydin, A. A.; Alaghband, G., Sequential
& Parallel Hybrid Approach for Non-Recursive Most Significant Digit Radix
Sort, Proceedings
of the IADIS Applied Computing 2013,
October 23-25, 2013, pp. 51-59, Fort Worth, Texas.
Mohammed, M.; Alaghband, G., An Improved Parallel Eight
Direction Prewitt Edge Detection Algorithm, Proceedings of the 17th
International Conference on Image Processing, Computer Vision, & Pattern
Recognition,
WorldComp 13, pp. 852-860, July 22-25, 2013, Las
Vegas, Nevada.
Vu, L.;
Alaghband, G., Mining Frequent Patterns Based on Data Characteristics, Proceedings
of the 2012 International Conference on Information & Knowledge Engineering,
in-print, WorldComp 12,
July 16-19, 2012, pp. 369-376, Las Vegas, Nevada.
Gnabasik,
D.; Alaghband, G., Proteomic Data Analysis: a Topological Approach, Proceedings
of the 2012 International Conference on Bioinformatics and Computational
Biology BIOCOMP, in-print, WorldComp
12, July 16-19, 2012, Las Vegas, Nevada.
Vu, L.;
Alaghband, G., High
Performance Frequent Pattern Mining on Multi-core Cluster, IEEE
Proceedings of the 2012 International Conference on Collaboration Technologies
and Systems (CTS 2012), pp. 630- 633, May 21-25, 2012, Denver, Colorado.
Gnabasik,
D.; Alaghband, G., Topological Analysis of Proteomic Data, IEEE Proceedings of the 2012
International Conference on Collaboration Technologies and Systems (CTS 2012),
pp. 634- 635, May 21-25, 2012, Denver, Colorado.
Vu, L.;
Alaghband, G., A Fast Algorithm Combining FP-Tree and TID-List for Frequent
Pattern Mining, Proceedings of the 2011 International Conference on
Information & Knowledge Engineering, pp. 472-477, WorldComp
11, July 18-21, 2011, Las Vegas, Nevada.
Alaghband,
G. , Relationship model: a network model for
integrating human expertise with systematic distributed processes, Journal
of Software Maintenance and Evolution: Research and Practice, Volume 23,
Issue 2, March 2011, Pages: 109135, Article first published online : 4 MAY
2010, DOI: 10.1002/smr.471 http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1532-0618/earlyview.