Victor D. Martinez and V. Manian, Jet Image Generation using Score Based and Consistency Diffusion Models, Phenomenology, University of Pittsburgh, May 19-21, 2025
Estefanía Alfaro-Mejía; Carlos J. Delgado; Vidya Manian, An Elliptic Kernel Unsupervised Autoencoder -Graph Convolutional Network Ensemble Model for Hyperspectral Unmixingy, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3 June 2025
- Delgado, C.J.; Alfaro-Mejía, E.; Manian, V.; O’Neill-Carrillo, E.; Andrade, F. Photovoltaic Power Generation Forecasting with Hidden Markov Model and Long Short-Term Memory in MISO and SISO Configurations. Energies 2024
- Gangapuram, H.; Manian, V. Electroencephalogram Functional Connectivity Analysis and Classification of Mental Arithmetic Working Memory Task. Signals 2024, 5, 296-325.
- Aguilera, A.; Manian, V. Artificial Intelligence Approach for Classifying Images of Upper-Atmospheric Transient Luminous Events. Sensors 2024, 24, 3208.
- Alfaro-Mejia, E.; Delgado, C.; Manian, V. An Elliptic Kernel Unsupervised Autoencoder-Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing. ArXiv 2024.
- Orozco, J.; Manian, V.; Malik, S. A multicategory jet image classification framework using deep neural network. ArXiv 2024.
- Katiyar, C., & Manian, V. Hyperspectral Multilevel GCN and CNN Feature Fusion for Change Detection. Authorea Preprints 2024.
- A Sparse Multiclass Motor Imagery EEG Classification Using 1D-ConvResNet, March 2023
- Graph Convolutional Network Using Adaptive Neighborhood Laplacian Matrix for Hyperspectral Images with Application to Rice Seed Image Classification, March 2023
- A Deep Learning Framework for Processing and Classification of Hyperspectral Rice Seed Images Grown under High Day and Night Temperatures, April 2023
- Gangapuram, H.; Manian, V. A Sparse Multiclass Motor Imagery EEG Classification Using 1D-ConvResNet. Signals 2023, 4, 235-250.
- Sridhar, S.; Romney, A.; Manian, V. A Deep Neural Network for Working Memory Load Prediction from EEG Ensemble Empirical Mode Decomposition. Information 2023, 14, 473.
- E. Alfaro-Mejia, V. Manian, J. Ortiz, and R. Tokars, A blind convolutional deep autoencoder for spectral unmixing of hyperspectral images over waterbodies, Frontiers, Earth Science, Vol. 11, 2023.
- Land use land cover labeling of GLOBE images using a deep learning fusion model, Sensors, 22(18),6895, August 2022
- Detection of target genes for drug repurposing to treat skeletal muscle atrophy in mice flown in spaceflight, Genes, 13(3), 473, March 2022
- Hyperspectral image labeling and classification using an ensemble semi-supervised machine learning approach, Sensors Journal, 22(4), 1623, Feb. 2022
- Optimizing seizure prediction from reduced scalp EEG channels based on spectral features and MAML, IEEE Access, Volume 9, pages 164348-164357, December 2021
- An integrative network science and artificial intelligence drug repurposing approach for muscle atrophy in spaceflight microgravity, Frontiers, Cell and Developmental Biology, 2021
- Spatial low-rank tensor factorization and unmixing of hyperspectral images, mdpi Computers Journal, 10(6), 78, 2021
- Detection of genes in Arabidopsis thaliana L. responding to DNA damage from radiation and other stressors in spaceflight, mdpi Genes Journal, 12(6), 938, 2021
- Network analysis of gene transcriptions of Arabidopsis thaliana in spaceflight mcirogravity, mdpi Genes Journal, 12(3), 337, 2021
- Network analysis of local gene regulators in Arabidopsis thaliana under spaceflight stress, mdpi Computers Journal, 10(2), 18, 2021
- EEG and deep learning based brain cognitive function classification, Mdpi Journal, Special Issue Feature Paper in Computers, 9(4), 104, December 2020
- Comparison of frontal-temporal channels in epilepsy seizure prediction based on EEMD-ReliefF and DNN, Mdpi Journal 9(4), 78, Sept. 2020
- Auditory source localization by time frequency analysis and classification of electroencephalogram signals, Biomedical Journal of Scientific & Technical Research, Vol. 19(5), July 2019
- Assessment of cognitive aging using an SSVEP-Based Brain-Computer Interface System, mdpi Journal of Big Data and Cognitive Computing, Vol. 3(2), May 2019
- J. Tantiongloc, D. A. Mesa, R. Ma, S. Kim, C. H. Alzate, J. Camacho, V. Manian and T. P. Coleman, “An information and control framework for optimizing user-complaint human computer interfaces,” JOURNAL of PROC. OF THE IEEE 105.2, 273-285, 2017
- A. Alarcon, M.R.Rwebangira, M.F. Chouika and V. Manian, “A new methodology based on level sets for target detection in hyperspectral images,” IEEE Trans. Geoscience and Remote Sensing, Vol. 54, No. 9, 5385-5396, 2016
- A. Sotomayor, J. Vidal, O. Medina and V. Manian, “Biodiversity assessment in coral reef benthic habitats using hyperspectral images,” IEEE SMC World Automation Congress, DOI: 10.1109/WAC.2016.7582946, IEEE, Oct. 2016.
- O. Medina and V. Manian, “A hierarchical semantic memory model for classification of motion capture data,” IEEE SMC World Automation Congress, DOI: 10.1109/WAC.2016.7582947, IEEE, Oct. 2016.
- O. Nieves and V. Manian, “Automatic person authentication using fewer channel EEG motor imagery,” IEEE SMC World Automation Congress, DOI: 10.1109/WAC.2016.7582945, IEEE, Oct. 2016.
- J. Camacho and V.Manian, “Real-time single channel EEG motor imagery based Brain Computer Interface, “IEEE SMC World Automation COngress, DOI:10.1109/WAC.2016.7582973, IEEE, Oct. 2016.
- O. Medina, V. Manian and J. D. Chinea, “Biodiversity assessment using hierarchical agglomerative clustering and spectral unmixing over hyperspectral images,” Sensors Journal, 13(10), 13949-13959, 2013.
- S. Huaman and V. Manian, “Object segmentation in hyperspectral images using active contours and graph cuts,” Intl. Journal of Remote Sensing, Vol. 33, NO. 4, pp. 1246-1263, Feb. 2012.
- S. Velasco-Forero and V. Manian, “Improving hyperspectral image classification using spatial preprocessing,” IEEE Trans. Geoscience and Remote Sensing Letters, Vol. 6, No. 2, pp. 297-301, April 2009.
- V. Manian and M. Velez-Reyes, “Support vector classification of land cov er and benthic habitat from hyperspectral iamges,” Intl. Journal of high speed electornics and systems, Vol. 18, NO. 2, pp. 337-348, June 2008.
- V. Manian and L. O. Jimenez, “Land cover and benthic habitat classification using texture features from multispectral and hyperspectral images,” Journal of Electronic Imaging, SPIE, VOl. 16, No. 2, 2007.
- V. Manian and A. Ross, “Face detection using statistical and multi-resolution texture features.” Multimedia Cyberspace Journal, Special Issue on Pattern Recognition and Bioinformatics, Vol. 3, No. 3, pp. 1-9, 2005.
- V. Manian and R. Vasquez, “Texture discrimination based on neural dynamics of visual perception.” In IEEE Joint Intl. conf. Neural Networks, Proceedings IEEE, Portland, Oregon, July 2003.
- V. Manian and R. Vasquez, “Approaches to color and texture based image classification.” Journal of Optical Engineering, SPIE, Vol. 41, No. 7, pp. 1480-1490, July 2002.
- V. Manian, R. Vásquez, and P. Katiyar, “Texture classification using logical operators.” IEEE Trans. on image processing, Vol. 9, No: 10, pp. 1693-1703, Oct. 2000.
- V. Manian and R. Vásquez, “Scaled and rotated texture classification using a class of basis functions.” Journal of Pattern Recognition, Vol. 31, No. 12, pp. 1937-1948, 1998