activity
20192021
most citedRadiological images and machine learning: trends, perspectives, and prospects

219 citations · 349 across the 6 of their papers we have counts for

collaborators

7 papers

cs.IT2021

Distance and Position Estimation in Visible Light Systems with RGB LEDs

Ilker Demirel, Sinan Gezici

In this manuscript, distance and position estimation problems are investigated for visible light positioning (VLP) systems with red-green-blue (RGB) light emitting diodes (LEDs). T…

cs.LG2020★ 76 cited

A Review of Hidden Markov Models and Recurrent Neural Networks for Event Detection and Localization in Biomedical Signals

Yassin Khalifa, Danilo Mandic, Ervin Sejdić

Biomedical signals carry signature rhythms of complex physiological processes that control our daily bodily activity. The properties of these rhythms indicate the nature of interac…

eess.IV2020★ 50 cited

Upper Esophageal Sphincter Opening Segmentation with Convolutional Recurrent Neural Networks in High Resolution Cervical Auscultation

Yassin Khalifa, Cara Donohue, James L. Coyle +1

Upper esophageal sphincter is an important anatomical landmark of the swallowing process commonly observed through the kinematic analysis of radiographic examinations that are vuln…

eess.SP2019★ 2 cited

Vertex-Frequency Graph Signal Processing: A review

Ljubisa Stankovic, Danilo P. Mandic, Milos Dakovic +4

Graph signal processing deals with signals which are observed on an irregular graph domain. While many approaches have been developed in classical graph theory to cluster vertices…

cs.LG2019

Single neuron-based neural networks are as efficient as dense deep neural networks in binary and multi-class recognition problems

Yassin Khalifa, Justin Hawks, Ervin Sejdic

Recent advances in neuroscience have revealed many principles about neural processing. In particular, many biological systems were found to reconfigure/recruit single neurons to ge…

eess.IV2019★ 219 cited

Radiological images and machine learning: trends, perspectives, and prospects

Zhenwei Zhang, Ervin Sejdic

The application of machine learning to radiological images is an increasingly active research area that is expected to grow in the next five to ten years. Recent advances in machin…