M. Ozay

发表

Task Guided Compositional Representation Learning for ZDA

Shuangwei Liu, Shuang Liu, M. Ozay, 2021, ArXiv.

Örüntü Analizi için Beyinde Ba˘ glanirlik Kestirimi Estimating Brain Connectivity for Pattern Analysis

Orhan Firat, Emre Aksan, M. Ozay, 2013 .

A New Fuzzy Stacked Generalization Technique for Deep learning and Analysis of its Performance pdf

Fatos T. Yarman-Vural, Mete Ozay, F. Yarman-Vural, 2012, ArXiv.

Feature Quantization for Defending Against Distortion of Images

Takayuki Okatani, M. Ozay, Zhun Sun, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Deep Depth Completion: A Survey

Tin Lun Lam, Chenyou Fan, M. Ozay, 2022, ArXiv.

Linear separability analysis for stacked generalization architecture

M. Ozay, Fatoş T. Yarman Vural, 2009, 2009 IEEE 17th Signal Processing and Communications Applications Conference.

FedNST: Federated Noisy Student Training for Automatic Speech Recognition

Karthikeyan P. Saravanan, A. Dobrowolska, M. Ozay, 2022, ArXiv.

Learning Deep Representations of Objects and Materials for Material Recognition

Takayuki Okatani, Yan Zhang, Xing Liu, 2016 .

Bring Evanescent Representations to Life in Lifelong Class Incremental Learning

M. Ozay, Marco Toldo, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A new hole density as a stability measure for boron fullerenes.

M. Ozay, S. Polad, 2013, Physical chemistry chemical physics : PCCP.

Deep Depth Completion: A Survey

Tin Lun Lam, Tin Lun Lam, Chenyou Fan, 2022, ArXiv.

Deep Depth Completion From Extremely Sparse Data: A Survey

Tin Lun Lam, Tin Lun Lam, Chenyou Fan, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence.

FedNST: Federated Noisy Student Training for Automatic Speech Recognition

Karthikeyan P. Saravanan, A. Dobrowolska, M. Ozay, 2022, Interspeech 2022.

Exploring the Gap between Collapsed & Whitened Features in Self-Supervised Learning

Bobby He, M. Ozay, 2022, ICML.

Feature Kernel Distillation

Bobby He, M. Ozay, 2022, ICLR.

pMCT: Patched Multi-Condition Training for Robust Speech Recognition

Karthikeyan P. Saravanan, A. Dobrowolska, M. Ozay, 2022, INTERSPEECH.

Encoding the local connectivity patterns of fMRI for cognitive task and state classification

M. Ozay, Itir Onal Ertugrul, Fatoş T. Yarman Vural, 2018, Brain Imaging and Behavior.

Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps With Accurate Object Boundaries

Takayuki Okatani, Yan Zhang, Mete Ozay, 2018, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).

Compositional Hierarchical Representation of Shape Manifolds for Classification of Non-manifold Shapes

Ales Leonardis, Mete Ozay, Jeremy L. Wyatt, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Building Detection With Decision Fusion

Fatos T. Yarman-Vural, Mete Ozay, Çaglar Senaras, 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Prototype Guided Federated Learning of Visual Feature Representations pdf

Mete Ozay, Umberto Michieli, M. Ozay, 2021, ArXiv.

Are All Users Treated Fairly in Federated Learning Systems?

Mete Ozay, Umberto Michieli, M. Ozay, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Data-free Dense Depth Distillation

Tin Lun Lam, Chenyou Fan, Hualie Jiang, 2022, ArXiv.

Improving Head Pose Estimation with a Combined Loss and Bounding Box Margin Adjustment

Takayuki Okatani, Mete Ozay, Zhun Sun, 2019, 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019).

LRA&LDRA: Rethinking Residual Predictions for Efficient Shadow Detection and Removal

Albert Saà-Garriga, M. Ozay, A. Drosou, 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

A New Fuzzy Stacked Generalization Technique and Analysis of its Performance

Fatos T. Yarman Vural, Mete Ozay, M. Ozay, 2012, 1204.0171.

Machine Learning Methods for Attack Detection in the Smart Grid

H. Vincent Poor, Sanjeev R. Kulkarni, Fatos T. Yarman-Vural, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Sparse Attack Construction and State Estimation in the Smart Grid: Centralized and Distributed Models

H. Vincent Poor, Sanjeev R. Kulkarni, Fatos T. Yarman-Vural, 2013, IEEE Journal on Selected Areas in Communications.

Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search pdf

Masanori Suganuma, Takayuki Okatani, Mete Ozay, 2018, ICML.

Hierarchical multi-resolution mesh networks for brain decoding

Fatos T. Yarman-Vural, Mete Ozay, Itir Önal, 2017, Brain Imaging and Behavior.

Mesh learning approach for brain data modeling

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2012, 2012 20th Signal Processing and Communications Applications Conference (SIU).

A New Approach to Design Symmetry Invariant Neural Networks

P. Skrzypczyński, M. Ozay, Piotr Kicki, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Distributed models for sparse attack construction and state vector estimation in the smart grid

H. Vincent Poor, Sanjeev R. Kulkarni, Fatos T. Yarman-Vural, 2012, 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm).

Semi-supervised Segmentation Fusion of Multi-spectral and Aerial Images

Mete Ozay, M. Ozay, 2014, 2014 22nd International Conference on Pattern Recognition.

Mesh learning for object classification using fMRI measurements

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2013, 2013 IEEE International Conference on Image Processing.

Mesh Learning for Classifying Cognitive Processes pdf

Fatos T. Yarman-Vural, Mete Ozay, Ilke Öztekin, 2012, ArXiv.

Federated Learning via Attentive Margin of Semantic Feature Representations

M. Ozay, Umberto Michieli, Marco Toldo, 2023, IEEE Internet of Things Journal.

Encoding the local connectivity patterns of fMRI for cognitive task and state classification

Mete Ozay, Itir Onal Ertugrul, Fatos T Yarman Vural, 2018, Brain Imaging and Behavior.

Hierarchical multi-resolution mesh networks for brain decoding

F. Yarman-Vural, M. Ozay, Itir Önal, 2016, Brain Imaging and Behavior.

Optimization on Submanifolds of Convolution Kernels in CNNs pdf

Takayuki Okatani, Mete Ozay, Takayuki Okatani, 2016, ArXiv.

Editorial: Novel perspectives and improvements in fMRI functional connectivity analysis methods used to investigate brain networks and cognitive mechanisms in humans

M. Ozay, 2023, Frontiers in Neuroscience.

Online Continual Learning in Keyword Spotting for Low-Resource Devices via Pooling High-Order Temporal Statistics

Pablo Peso Parada, M. Ozay, Umberto Michieli, 2023, ArXiv.

Online Continual Learning for Robust Indoor Object Recognition

M. Ozay, Umberto Michieli, 2023, arXiv.org.

Analyzing the information distribution in the fMRI measurements by estimating the degree of locality

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Information distribution analysis in the fMRI measurements with degree of locality estimation

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2013, 2013 21st Signal Processing and Communications Applications Conference (SIU).

A hierarchical approach for joint multi-view object pose estimation and categorization

Krzysztof Walas, Ales Leonardis, Mete Ozay, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

A Graph Theoretic Approach for Object Shape Representation in Compositional Hierarchies Using a Hybrid Generative-Descriptive Model

Ales Leonardis, Mete Ozay, Jeremy L. Wyatt, 2014, ECCV.

Integrating deep features for material recognition

Takayuki Okatani, Yan Zhang, Xing Liu, 2015, 2016 23rd International Conference on Pattern Recognition (ICPR).

HyperNetworks with statistical filtering for defending adversarial examples pdf

Takayuki Okatani, Mete Ozay, Zhun Sun, 2017, ArXiv.

A theoretical analysis of feature fusion in Stacked Generalization

Mete Ozay, Fatos T. Yarman Vural, M. Ozay, 2009, 2009 IEEE 17th Signal Processing and Communications Applications Conference.

Smarter security in the smart grid

H. Vincent Poor, Sanjeev R. Kulkarni, Fatos T. Yarman-Vural, 2012, 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm).

A Model for Every User and Budget: Label-Free and Personalized Mixed-Precision Quantization

M. Ozay, Umberto Michieli, Edward Fish, 2023, INTERSPEECH 2023.

Encoding the Local Connectivity Patterns of fMRI for Cognitive State Classification pdf

Fatos T. Yarman-Vural, Itir Onal Ertugrul, Mete Ozay, 2016, ArXiv.

Fine-grained Optimization of Deep Neural Networks

Mete Ozay, M. Ozay, 2019, NeurIPS.

A New Approach to Design Symmetry Invariant Neural Networks pdf

Piotr Kicki, Mete Ozay, Piotr Skrzypczy'nski, 2020, 2021 International Joint Conference on Neural Networks (IJCNN).

Linear Discriminant Generative Adversarial Networks pdf

Takayuki Okatani, Mete Ozay, Zhun Sun, 2017, ArXiv.

Joint Adversarial Example and False Data Injection Attacks for State Estimation in Power Systems

M. Ozay, Buhong Wang, Jiwei Tian, 2021, IEEE Transactions on Cybernetics.

Gender classification using mesh networks on multiresolution multitask fMRI data

M. Ozay, Itir Onal Ertugrul, Fatoş T. Yarman Vural, 2019, Brain Imaging and Behavior.

Discriminative Functional Connectivity Measures for Brain Decoding pdf

Orhan Firat, Mete Ozay, Ilke Oztekin, 2014, ArXiv.

Functional Mesh Learning for pattern analysis of cognitive processes

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2013, 2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing.

Representation of cognitive processes using the minimum spanning tree of local meshes

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Enhancing Local Linear Models Using Functional Connectivity for Brain State Decoding

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2013, Int. J. Cogn. Informatics Nat. Intell..

Cognitive process representation with minimum spanning tree of local meshes

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2013, 2013 21st Signal Processing and Communications Applications Conference (SIU).

Improving Robustness of Feature Representations to Image Deformations using Powered Convolution in CNNs pdf

Takayuki Okatani, Mete Ozay, Zhun Sun, 2017, ArXiv.

Task guided representation learning using compositional models for zero-shot domain adaptation

Shuangwei Liu, M. Ozay, 2023, Neural Networks.

A New Representation of fMRI Signal by a Set of Local Meshes for Brain Decoding

Mete Ozay, Ilke Oztekin, Fatos T. Yarman Vural, 2017, IEEE Transactions on Signal and Information Processing over Networks.

Modeling the Sequence of Brain Volumes by Local Mesh Models for Brain Decoding pdf

Fatos T. Yarman-Vural, Mete Ozay, Itir Önal, 2016, ArXiv.

Functional Mesh Model with Temporal Measurements for brain decoding

Fatos T. Yarman-Vural, Mete Ozay, Itir Önal, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

An information theoretic approach to classify cognitive states using fMRI

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2013, 13th IEEE International Conference on BioInformatics and BioEngineering.

Feature Quantization for Defending Against Distortion of Images

Takayuki Okatani, Xing Liu, Yan Zhang, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Data-Free Model Pruning at Initialization via Expanders

M. Ozay, Umberto Michieli, James Stewart, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Dense depth distillation with out-of-distribution simulated images

Tin Lun Lam, Chenyou Fan, Hualie Jiang, 2022, Knowl. Based Syst..

Functional networks of anatomic brain regions

Fatos T. Yarman-Vural, Orhan Firat, Mete Ozay, 2014, 2014 IEEE 13th International Conference on Cognitive Informatics and Cognitive Computing.

Training CNNs With Normalized Kernels

Takayuki Okatani, Mete Ozay, Takayuki Okatani, 2018, AAAI.