b'M. Ozay'

research

∙ 07/25/2023

On-Device Speaker Anonymization of Acoustic Embeddings for ASR based onFlexible Location Gradient Reversal Layer

Smart devices serviced by large-scale AI models necessitates user data t...

0 Md Asif Jalal, et al. ∙

research

∙ 07/24/2023

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

Keyword Spotting (KWS) models on embedded devices should adapt fast to n...

0 Umberto Michieli, et al. ∙

research

∙ 07/24/2023

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

Recent advancement in Automatic Speech Recognition (ASR) has produced la...

0 Edward Fish, et al. ∙

research

∙ 07/19/2023

Online Continual Learning for Robust Indoor Object Recognition

Vision systems mounted on home robots need to interact with unseen class...

0 Umberto Michieli, et al. ∙

research

∙ 07/11/2022

pMCT: Patched Multi-Condition Training for Robust Speech Recognition

We propose a novel Patched Multi-Condition Training (pMCT) method for ro...

0 Pablo Peso Parada, et al. ∙

research

∙ 06/06/2022

FedNST: Federated Noisy Student Training for Automatic Speech Recognition

Federated Learning (FL) enables training state-of-the-art Automatic Spee...

0 Haaris Mehmood, et al. ∙

research

∙ 05/11/2022

Deep Depth Completion: A Survey

Depth completion aims at predicting dense pixel-wise depth from a sparse...

119 Junjie Hu, et al. ∙

research

∙ 03/12/2022

A Mixed Quantization Network for Computationally Efficient Mobile Inverse Tone Mapping

Recovering a high dynamic range (HDR) image from a single low dynamic ra...

0 Juan Borrego-Carazo, et al. ∙

research

∙ 02/11/2022

Adversarial Attacks and Defense Methods for Power Quality Recognition

Vulnerability of various machine learning methods to adversarial example...

19 Jiwei Tian, et al. ∙

research

∙ 09/13/2021

Task Guided Compositional Representation Learning for ZDA

Zero-shot domain adaptation (ZDA) methods aim to transfer knowledge abou...

0 Shuang Liu, et al. ∙

research

∙ 05/19/2021

Prototype Guided Federated Learning of Visual Feature Representations

Federated Learning (FL) is a framework which enables distributed model t...

0 Umberto Michieli, et al. ∙

research

∙ 12/11/2020

A New Neural Network Architecture Invariant to the Action of Symmetry Subgroups

We propose a computationally efficient G-invariant neural network that a...

0 Piotr Kicki, et al. ∙

research

∙ 12/07/2020

Learning from Experience for Rapid Generation of Local Car Maneuvers

Being able to rapidly respond to the changing scenes and traffic situati...

0 Piotr Kicki, et al. ∙

research

∙ 02/18/2020

A Computationally Efficient Neural Network Invariant to the Action of Symmetry Subgroups

We introduce a method to design a computationally efficient G-invariant ...

0 Piotr Kicki, et al. ∙

research

∙ 05/22/2019

Fine-grained Optimization of Deep Neural Networks

In recent studies, several asymptotic upper bounds on generalization err...

0 M. Ozay, et al. ∙

research

∙ 05/14/2019

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

We address a problem of estimating pose of a person's head from its RGB ...

0 Mingzhen Shao, et al. ∙

research

∙ 03/23/2018

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

We revisit the problem of estimating depth of a scene from its single RG...

4 Junjie Hu, et al. ∙

research

∙ 03/01/2018

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

Researchers have applied deep neural networks to image restoration tasks...

0 Masanori Suganuma, et al. ∙

research

∙ 01/24/2018

Deep Structured Energy-Based Image Inpainting

In this paper, we propose a structured image inpainting method employing...

0 Fazil Altinel, et al. ∙

research

∙ 12/12/2017

A vision based system for underwater docking

Autonomous underwater vehicles (AUVs) have been deployed for underwater ...

0 Shuang Liu, et al. ∙

research

∙ 11/06/2017

HyperNetworks with statistical filtering for defending adversarial examples

Deep learning algorithms have been known to be vulnerable to adversarial...

0 Zhun Sun, et al. ∙

research

∙ 07/25/2017

Linear Discriminant Generative Adversarial Networks

We develop a novel method for training of GANs for unsupervised and clas...

0 Zhun Sun, et al. ∙

research

∙ 07/25/2017

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

In this work, we address the problem of improvement of robustness of fea...

0 Zhun Sun, et al. ∙

research

∙ 06/14/2017

Information Potential Auto-Encoders

In this paper, we suggest a framework to make use of mutual information ...

0 Yan Zhang, et al. ∙

research

∙ 04/03/2017

Truncating Wide Networks using Binary Tree Architectures

Recent study shows that a wide deep network can obtain accuracy comparab...

0 Yan Zhang, et al. ∙

research

∙ 01/22/2017

Optimization on Product Submanifolds of Convolution Kernels

Recent advances in optimization methods used for training convolutional ...

0 M. Ozay, et al. ∙

research

∙ 10/22/2016

Optimization on Submanifolds of Convolution Kernels in CNNs

Kernel normalization methods have been employed to improve robustness of...

0 M. Ozay, et al. ∙

research

∙ 10/17/2016

Encoding the Local Connectivity Patterns of fMRI for Cognitive State Classification

In this work, we propose a novel framework to encode the local connectiv...

0 Itir Onal Ertugrul, et al. ∙

research

∙ 07/12/2016

Hierarchical Multi-resolution Mesh Networks for Brain Decoding

We propose a new framework, called Hierarchical Multi-resolution Mesh Ne...

0 Itir Onal Ertugrul, et al. ∙

research

∙ 03/03/2016

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

We represent the sequence of fMRI (Functional Magnetic Resonance Imaging...

0 Itir Onal, et al. ∙

research

∙ 11/30/2015

Design of Kernels in Convolutional Neural Networks for Image Classification

Despite the effectiveness of Convolutional Neural Networks (CNNs) for im...

0 Zhun Sun, et al. ∙

research

∙ 03/04/2015

A Hierarchical Approach for Joint Multi-view Object Pose Estimation and Categorization

We propose a joint object pose estimation and categorization approach wh...

0 M. Ozay, et al. ∙

research

∙ 02/18/2015

Fusion of Image Segmentation Algorithms using Consensus Clustering

A new segmentation fusion method is proposed that ensembles the output o...

0 M. Ozay, et al. ∙

research

∙ 02/17/2015

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

A Semi-supervised Segmentation Fusion algorithm is proposed using consen...

0 M. Ozay, et al. ∙

research

∙ 01/21/2015

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

A graph theoretic approach is proposed for object shape representation i...

0 Umit Rusen Aktas, et al. ∙

research

∙ 02/23/2014

Discriminative Functional Connectivity Measures for Brain Decoding

We propose a statistical learning model for classifying cognitive proces...

0 Orhan Firat, et al. ∙

research

∙ 05/10/2012

Mesh Learning for Classifying Cognitive Processes

A relatively recent advance in cognitive neuroscience has been multi-vox...

0 M. Ozay, et al. ∙

M. Ozay

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