11 citations · 12 across the 6 of their papers we have counts for
6 papers
SSplain: Sparse and Smooth Explainer for Retinopathy of Prematurity Classification
Elifnur Sunger, Tales Imbiriba, Peter Campbell +3
Neural networks are frequently used in medical diagnosis. However, due to their black-box nature, model explainers are used to help clinicians understand better and trust model out…
MarkovType: A Markov Decision Process Strategy for Non-Invasive Brain-Computer Interfaces Typing Systems
Elifnur Sunger, Yunus Bicer, Deniz Erdogmus +1
Brain-Computer Interfaces (BCIs) help people with severe speech and motor disabilities communicate and interact with their environment using neural activity. This work focuses on t…
Fast and Expressive Gesture Recognition using a Combination-Homomorphic Electromyogram Encoder
Niklas Smedemark-Margulies, Yunus Bicer, Elifnur Sunger +5
We study the task of gesture recognition from electromyography (EMG), with the goal of enabling expressive human-computer interaction at high accuracy, while minimizing the time re…
Tubular Curvature Filter: Pointwise Curvature Calculation for Tubular Objects in Images
Elifnur Sunger, Beyza Kalkanli, Veysi Yildiz +4
Purpose: Accurate estimation of blood vessel tortuosity from medical images is an extremely important and challenging task. It is particularly relevant in the context of retinopath…
A Multi-label Classification Approach to Increase Expressivity of EMG-based Gesture Recognition
Niklas Smedemark-Margulies, Yunus Bicer, Elifnur Sunger +5
Objective: The objective of the study is to efficiently increase the expressivity of surface electromyography-based (sEMG) gesture recognition systems. Approach: We use a problem t…
User Training with Error Augmentation for Electromyogram-based Gesture Classification
Yunus Bicer, Niklas Smedemark-Margulies, Basak Celik +7
We designed and tested a system for real-time control of a user interface by extracting surface electromyographic (sEMG) activity from eight electrodes in a wrist-band configuratio…