655 citations · 881 across the 8 of their papers we have counts for
9 papers
Encoding the Local Connectivity Patterns of fMRI for Cognitive State Classification
Itir Onal Ertugrul, Mete Ozay, Fatos T. Yarman Vural
In this work, we propose a novel framework to encode the local connectivity patterns of brain, using Fisher Vectors (FV), Vector of Locally Aggregated Descriptors (VLAD) and Bag-of…
Hierarchical Multi-resolution Mesh Networks for Brain Decoding
Itir Onal Ertugrul, Mete Ozay, Fatos Tunay Yarman Vural
We propose a new framework, called Hierarchical Multi-resolution Mesh Networks (HMMNs), which establishes a set of brain networks at multiple time resolutions of fMRI signal to rep…
Modeling the Sequence of Brain Volumes by Local Mesh Models for Brain Decoding
Itir Onal, Mete Ozay, Eda Mizrak +2
We represent the sequence of fMRI (Functional Magnetic Resonance Imaging) brain volumes recorded during a cognitive stimulus by a graph which consists of a set of local meshes. The…
Machine Learning Methods for Attack Detection in the Smart Grid
Mete Ozay, Inaki Esnaola, Fatos T. Yarman Vural +2
Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online sett…
Fusion of Image Segmentation Algorithms using Consensus Clustering
Mete Ozay, Fatos T. Yarman Vural, Sanjeev R. Kulkarni +1
A new segmentation fusion method is proposed that ensembles the output of several segmentation algorithms applied on a remotely sensed image. The candidate segmentation sets are pr…
Sparse Attack Construction and State Estimation in the Smart Grid: Centralized and Distributed Models
Mete Ozay, Inaki Esnaola, Fatos T. Yarman Vural +2
New methods that exploit sparse structures arising in smart grid networks are proposed for the state estimation problem when data injection attacks are present. First, construction…
Discriminative Functional Connectivity Measures for Brain Decoding
Orhan Firat, Mete Ozay, Ilke Oztekin +1
We propose a statistical learning model for classifying cognitive processes based on distributed patterns of neural activation in the brain, acquired via functional magnetic resona…
Mesh Learning for Classifying Cognitive Processes
Mete Ozay, Ilke Öztekin, Uygar Öztekin +1
A relatively recent advance in cognitive neuroscience has been multi-voxel pattern analysis (MVPA), which enables researchers to decode brain states and/or the type of information…
A New Fuzzy Stacked Generalization Technique and Analysis of its Performance
Mete Ozay, Fatos T. Yarman Vural
In this study, a new Stacked Generalization technique called Fuzzy Stacked Generalization (FSG) is proposed to minimize the difference between N -sample and large-sample classifica…