138 citations · 239 across the 5 of their papers we have counts for
5 papers
EndoSensorFusion: Particle Filtering-Based Multi-sensory Data Fusion with Switching State-Space Model for Endoscopic Capsule Robots
Mehmet Turan, Yasin Almalioglu, Hunter Gilbert +3
A reliable, real time multi-sensor fusion functionality is crucial for localization of actively controlled capsule endoscopy robots, which are an emerging, minimally invasive diagn…
Endo-VMFuseNet: Deep Visual-Magnetic Sensor Fusion Approach for Uncalibrated, Unsynchronized and Asymmetric Endoscopic Capsule Robot Localization Data
Mehmet Turan, Yasin Almalioglu, Hunter Gilbert +3
In the last decade, researchers and medical device companies have made major advances towards transforming passive capsule endoscopes into active medical robots. One of the major c…
Deep EndoVO: A Recurrent Convolutional Neural Network (RCNN) based Visual Odometry Approach for Endoscopic Capsule Robots
Mehmet Turan, Yasin Almalioglu, Helder Araujo +2
Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologi…
A Non-Rigid Map Fusion-Based RGB-Depth SLAM Method for Endoscopic Capsule Robots
Mehmet Turan, Yasin Almalioglu, Helder Araujo +2
In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is considered as a minimally invasive novel diagnostic technology to inspect the entire GI…
A Deep Learning Based 6 Degree-of-Freedom Localization Method for Endoscopic Capsule Robots
Mehmet Turan, Yasin Almalioglu, Ender Konukoglu +1
We present a robust deep learning based 6 degrees-of-freedom (DoF) localization system for endoscopic capsule robots. Our system mainly focuses on localization of endoscopic capsul…