1 | YOLCU ÖZTEL GÖZDE - Vision-based Road Segmentation for Intelligent Vehicles using Deep Convolutional Neural Networks - DOI : 10.1109/INISTA52262.2021 - İngilizce - 2021 |
2 | ÖZTEL İSMAİL,YOLCU ÖZTEL GÖZDE,ÖZ CEMİL - Performance Comparison of Transfer Learning and Training from Scratch Approaches for Deep Facial Expression Recognition - İngilizce - 2019 |
3 | ÖZTEL İSMAİL,YOLCU ÖZTEL GÖZDE,Ersoy İlker,White Tommi,Bunyak Filiz - Deep Learning-based Mitochondria Segmentation in Electron Microscopy Volumes - İngilizce - 2018 |
4 | YOLCU ÖZTEL GÖZDE,ÖZTEL İSMAİL,KAZAN SERAP,ÖZ CEMİL,Palaniappan Kannappan,Lever Teresa,Bunyak Filiz - Deep learning-based facial expression recognition for monitoring neurological disorders - DOI : 10.1109/BIBM.2017.8217907 - İngilizce - 2017 |
5 | YOLCU ÖZTEL GÖZDE,ÖZTEL İSMAİL,KAZAN SERAP,ÖZ CEMİL,Bunyak Filiz - Facial Component Segmentation using Convolutional Neural Network - İngilizce - 2017 |
6 | ÖZTEL İSMAİL,YOLCU ÖZTEL GÖZDE,ÖZ CEMİL,KAZAN SERAP - Facial Expression Recognition with Robust Feature Selecetion - İngilizce - 2017 |
7 | ÖZTEL İSMAİL,YOLCU ÖZTEL GÖZDE,Ersoy İlker,White Tommi,Bunyak Filiz - Segmentation of Mitochondria in Electron Microscopy Volumes using Deep Learning - İngilizce - 2017 |
8 | ÖZTEL İSMAİL,YOLCU ÖZTEL GÖZDE,Ersoy İlker,White Tommi,Bunyak Filiz - Mitochondria segmentation in electron microscopy volumes using deep convolutional neural network - DOI : 10.1109/BIBM.2017.8217827 - İngilizce - 2017 |
9 | KAZAN SERAP,YOLCU GÖZDE,TAŞBAŞI NEVZAT - DT CWT Based Face Recognition Using PNN and SVM - İngilizce - 2015 |
10 | ÖZ CEMİL,KAZAN SERAP,YOLCU ÖZTEL GÖZDE - Real Time Hand Shape Recognition Wıth Ann Using Kinect - İngilizce - 2014 |
11 | YOLCU ÖZTEL GÖZDE,ÖZ CEMİL,TAŞCI TUĞRUL - Developing and Establishing a Painting Program Controlled by Hand Motions Using Kinect - İngilizce - 2014 |
12 | ADAK MUHAMMED FATİH,YOLCU ÖZTEL GÖZDE,YUMUŞAK NEJAT - Finding Cuts Point of Textile Products Using Blob Analysis Method - İngilizce - 2013 |
İletişim
gyolcu@sakarya.edu.tr+90 (264) 295 32 39