Deniz Erdogmus

research

∙ 09/13/2023

A Multi-label Classification Approach to Increase Expressivity of EMG-based Gesture Recognition

Objective: The objective of the study is to efficiently increase the exp...

0 Niklas Smedemark-Margulies, et al. ∙

research

∙ 07/22/2023

A Vision for Cleaner Rivers: Harnessing Snapshot Hyperspectral Imaging to Detect Macro-Plastic Litter

Plastic waste entering the riverine harms local ecosystems leading to ne...

0 Nathaniel Hanson, et al. ∙

research

∙ 07/13/2023

Corticomorphic Hybrid CNN-SNN Architecture for EEG-based Low-footprint Low-latency Auditory Attention Detection

In a multi-speaker "cocktail party" scenario, a listener can selectively...

0 Richard Gall, et al. ∙

research

∙ 07/03/2022

Pregrasp Object Material Classification by a Novel Gripper Design with Integrated Spectroscopy

Robots benefit from being able to classify objects they interact with or...

0 Nathaniel Hanson, et al. ∙

research

∙ 05/12/2022

Neural Network-based OFDM Receiver for Resource Constrained IoT Devices

Orthogonal Frequency Division Multiplexing (OFDM)-based waveforms are us...

0 Nasim Soltani, et al. ∙

research

∙ 05/02/2022

Deep Learning Framework for Real-time Fetal Brain Segmentation in MRI

Fetal brain segmentation is an important first step for slice-level moti...

0 Razieh Faghihpirayesh, et al. ∙

research

∙ 04/13/2022

Hybrid Neural Network Augmented Physics-based Models for Nonlinear Filtering

In this paper we present a hybrid neural network augmented physics-based...

0 Tales Imbiriba, et al. ∙

research

∙ 12/17/2021

AutoTransfer: Subject Transfer Learning with Censored Representations on Biosignals Data

We provide a regularization framework for subject transfer learning in w...

0 Niklas Smedemark-Margulies, et al. ∙

research

∙ 11/02/2021

Equivariant Deep Dynamical Model for Motion Prediction

Learning representations through deep generative modeling is a powerful ...

0 Bahar Azari, et al. ∙

research

∙ 10/12/2021

Cubature Kalman Filter Based Training of Hybrid Differential Equation Recurrent Neural Network Physiological Dynamic Models

Modeling biological dynamical systems is challenging due to the interdep...

0 Ahmet Demirkaya, et al. ∙

research

∙ 10/03/2021

Efficient Modeling of Morphing Wing Flight Using Neural Networks and Cubature Rules

Fluidic locomotion of flapping Micro Aerial Vehicles (MAVs) can be very ...

0 Paul Ghanem, et al. ∙

research

∙ 07/26/2021

Circular-Symmetric Correlation Layer based on FFT

Despite the vast success of standard planar convolutional neural network...

0 Bahar Azari, et al. ∙

research

∙ 06/16/2021

EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals

Convolutional neural networks (CNN) have been frequently used to extract...

0 Andac Demir, et al. ∙

research

∙ 05/04/2021

On the Sample Complexity of Rank Regression from Pairwise Comparisons

We consider a rank regression setting, in which a dataset of N samples w...

0 Berkan Kadioglu, et al. ∙

research

∙ 05/01/2021

Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction Networks

Feature ranking and selection is a widely used approach in various appli...

0 Ozan Özdenizci, et al. ∙

research

∙ 04/26/2021

End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning

State-of-the-art human-in-the-loop robot grasping is hugely suffered by ...

0 Mohammadreza Sharif, et al. ∙

research

∙ 04/19/2021

Segmentation and Classification of EMG Time-Series During Reach-to-Grasp Motion

The electromyography (EMG) signals have been widely utilized in human ro...

0 Mo Han, et al. ∙

research

∙ 04/17/2021

Model-Based Deep Autoencoder Networks for Nonlinear Hyperspectral Unmixing

Autoencoder (AEC) networks have recently emerged as a promising approach...

0 Haoqing Li, et al. ∙

research

∙ 04/08/2021

Multimodal Fusion of EMG and Vision for Human Grasp Intent Inference in Prosthetic Hand Control

For lower arm amputees, robotic prosthetic hands offer the promise to re...

0 Mehrshad Zandigohar, et al. ∙

research

∙ 02/17/2021

EEG-based Texture Roughness Classification in Active Tactile Exploration with Invariant Representation Learning Networks

During daily activities, humans use their hands to grasp surrounding obj...

0 Ozan Özdenizci, et al. ∙

research

∙ 02/16/2021

On the use of generative deep neural networks to synthesize artificial multichannel EEG signals

Recent promises of generative deep learning lately brought interest to i...

0 Ozan Özdenizci, et al. ∙

research

∙ 01/13/2021

NetCut: Real-Time DNN Inference Using Layer Removal

Deep Learning plays a significant role in assisting humans in many aspec...

0 Mehrshad Zandigohar, et al. ∙

research

∙ 01/13/2021

Towards Creating a Deployable Grasp Type Probability Estimator for a Prosthetic Hand

For lower arm amputees, prosthetic hands promise to restore most of phys...

7 Mehrshad Zandigohar, et al. ∙

research

∙ 09/28/2020

Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders

Human computer interaction (HCI) involves a multidisciplinary fusion of ...

0 Mo Han, et al. ∙

research

∙ 08/26/2020

Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction

Recent developments in biosignal processing have enabled users to exploi...

5 Mo Han, et al. ∙

research

∙ 07/30/2020

Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry

Systems that are based on recursive Bayesian updates for classification ...

7 Aziz Koçanaoğulları, et al. ∙

research

∙ 07/02/2020

AutoBayes: Automated Inference via Bayesian Graph Exploration for Nuisance-Robust Biosignal Analysis

Learning data representations that capture task-related features, but ar...

74 Andac Demir, et al. ∙

research

∙ 04/30/2020

Prediction of Epilepsy Development in Traumatic Brain Injury Patients from Diffusion Weighted MRI

Post-traumatic epilepsy (PTE) is a life-long complication of traumatic b...

0 Md Navid Akbar, et al. ∙

research

∙ 04/15/2020

Disentangled Adversarial Transfer Learning for Physiological Biosignals

Recent developments in wearable sensors demonstrate promising results fo...

9 Mo Han, et al. ∙

research

∙ 04/07/2020

Active Recursive Bayesian Inference with Posterior Trajectory Analysis Using α-Divergence

Recursive Bayesian inference (RBI) provides optimal Bayesian latent vari...

4 Yeganeh M. Marghi, et al. ∙

research

∙ 02/14/2020

Mapping Motor Cortex Stimulation to Muscle Responses: A Deep Neural Network Modeling Approach

A deep neural network (DNN) that can reliably model muscle responses fro...

23 Md Navid Akbar, et al. ∙

research

∙ 10/02/2019

User-Adaptive Text Entry for Augmentative and Alternative Communication

The viability of an Augmentative and Alternative Communication device of...

0 Matt Higger, et al. ∙

research

∙ 07/22/2019

Adversarial Feature Learning in Brain Interfacing: An Experimental Study on Eliminating Drowsiness Effects

Across- and within-recording variabilities in electroencephalographic (E...

0 Ozan Özdenizci, et al. ∙

research

∙ 03/28/2019

Information Theoretic Feature Transformation Learning for Brain Interfaces

Objective: A variety of pattern analysis techniques for model training i...

0 Ozan Özdenizci, et al. ∙

research

∙ 03/27/2019

Adversarial Deep Learning in EEG Biometrics

Deep learning methods for person identification based on electroencephal...

1 Ozan Özdenizci, et al. ∙

research

∙ 01/18/2019

Accelerated Experimental Design for Pairwise Comparisons

Pairwise comparison labels are more informative and less variable than c...

0 Yuan Guo, et al. ∙

research

∙ 12/17/2018

Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders

We introduce adversarial neural networks for representation learning as ...

1 Ozan Özdenizci, et al. ∙

research

∙ 09/15/2018

Time-Series Prediction of Proximal Aggression Onset in Minimally-Verbal Youth with Autism Spectrum Disorder Using Physiological Biosignals

It has been suggested that changes in physiological arousal precede pote...

0 Ozan Özdenizci, et al. ∙

research

∙ 09/15/2018

Hierarchical Graphical Models for Context-Aware Hybrid Brain-Machine Interfaces

We present a novel hierarchical graphical model based context-aware hybr...

0 Ozan Özdenizci, et al. ∙

research

∙ 08/05/2018

Structured Adversarial Attack: Towards General Implementation and Better Interpretability

When generating adversarial examples to attack deep neural networks (DNN...

16 Kaidi Xu, et al. ∙

research

∙ 05/21/2018

Invariant Representations from Adversarially Censored Autoencoders

We combine conditional variational autoencoders (VAE) with adversarial c...

1 Ye Wang, et al. ∙

research

∙ 03/28/2018

Tversky as a Loss Function for Highly Unbalanced Image Segmentation using 3D Fully Convolutional Deep Networks

Fully convolutional deep neural networks have been asserted to be fast a...

0 Seyed Raein Hashemi, et al. ∙

research

∙ 03/15/2018

Real-time Deep Registration With Geodesic Loss

With an aim to increase the capture range and accelerate the performance...

0 Seyed Sadegh Mohseni Salehi, et al. ∙

research

∙ 10/25/2017

Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning

Brain segmentation is a fundamental first step in neuroimage analysis. I...

0 Seyed Sadegh Mohseni Salehi, et al. ∙

research

∙ 06/18/2017

Tversky loss function for image segmentation using 3D fully convolutional deep networks

Fully convolutional deep neural networks carry out excellent potential f...

0 Seyed Sadegh Mohseni Salehi, et al. ∙

research

∙ 03/06/2017

Auto-context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging

Brain extraction or whole brain segmentation is an important first step ...

0 Seyed Sadegh Mohseni Salehi, et al. ∙

research

∙ 05/27/2016

Asymptotic Analysis of Objectives based on Fisher Information in Active Learning

Obtaining labels can be costly and time-consuming. Active learning allow...

0 Jamshid Sourati, et al. ∙

research

∙ 04/06/2016

Manifold unwrapping using density ridges

Research on manifold learning within a density ridge estimation framewor...

0 Jonas Nordhaug Myhre, et al. ∙

Deniz Erdogmus

Featured Co-authors