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20192022
most citedCoupled Support Tensor Machine Classification for Multimodal Neuroimaging Data

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

stat.ML20221 cited

Coupled Support Tensor Machine Classification for Multimodal Neuroimaging Data

Li Peide, Seyyid Emre Sofuoglu, Tapabrata Maiti +1

Multimodal data arise in various applications where information about the same phenomenon is acquired from multiple sensors and across different imaging modalities. Learning from m…

cs.LG2020

Low-rank on Graphs plus Temporally Smooth Sparse Decomposition for Anomaly Detection in Spatiotemporal Data

Seyyid Emre Sofuoglu, Selin Aviyente

Anomaly detection in spatiotemporal data is a challenging problem encountered in a variety of applications including hyperspectral imaging, video surveillance, and urban traffic mo…

eess.SP2020

GLOSS: Tensor-Based Anomaly Detection in Spatiotemporal Urban Traffic Data

Seyyid Emre Sofuoglu, Selin Aviyente

Anomaly detection in spatiotemporal data is a challenging problem encountered in a variety of applications including hyperspectral imaging, video surveillance and urban traffic mon…

eess.IV2019

Graph Regularized Tensor Train Decomposition

Seyyid Emre Sofuoglu, Selin Aviyente

With the advances in data acquisition technology, tensor objects are collected in a variety of applications including multimedia, medical and hyperspectral imaging. As the dimensio…

eess.SP2019

Multi-Branch Tensor Network Structure for Tensor-Train Discriminant Analysis

Seyyid Emre Sofuoglu, Selin Aviyente

Higher-order data with high dimensionality arise in a diverse set of application areas such as computer vision, video analytics and medical imaging. Tensors provide a natural tool…