Leonardo O. Iheme
Leonardo O. Iheme
EPAM Systems
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Cited by
Cited by
Longitudinal multiple sclerosis lesion segmentation: resource and challenge
A Carass, S Roy, A Jog, JL Cuzzocreo, E Magrath, A Gherman, J Button, ...
NeuroImage 148, 77-102, 2017
Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge
DM Cash, C Frost, LO Iheme, D Ünay, M Kandemir, J Fripp, O Salvado, ...
Neuroimage 123, 149-164, 2015
Coded QPSK-OFDM for data transmission over fading channels
NKJ Dushantha, OI Leonardo, Aİ Erhan
2010 Fifth International Conference on Information and Automation for …, 2010
Artificial neural networks in customer segmentation
Ş Ozan, LO Iheme
2019 27th Signal Processing and Communications Applications Conference (SIU …, 2019
Concordance between computer-based neuroimaging findings and expert assessments in dementia grading
LO Iheme, D Ünay, O Başkaya, A Şennaz, M Kandemir, ZB Yalçıner, ...
2013 21st Signal Processing and Communications Applications Conference (SIU …, 2013
Analysis of detected silent segments in call center recordings
Ş Ozan, LO Iheme
2019 International Artificial Intelligence and Data Processing Symposium …, 2019
Multiclass Digital Audio Segmentation with MFCC Features using Naive Bayes and SVM Classifiers
LO Iheme, Ş Ozan
Innovations in Intelligent Systems and Applications Conference (ASYU), 1-5, 2020
Feature Selection for Anomaly Detection in Call Center Data
LO Iheme, Ş Ozan
2019 11th International Conference on Electrical and Electronics Engineering …, 2019
Un-coded versus Coded QPSK-OFDM Performance over Rayleigh Fading Channels and DL-PUSC Subchannelization for OFDMA
LO Iheme
Eastern Mediterranean University, 2010
Automatic white matter hyperintensity segmentation using FLAIR MRI: The MS lesion segmentation challenge
LO Iheme, D Unay
NeuroImage 28 (3), 607-17, 2005
A novel semi-supervised framework for call center agent malpractice detection via neural feature learning
LO Iheme, Ş Ozan
Expert Systems with Applications 208, 118173, 2022
MITNET: a novel dataset and a two-stage deep learning approach for mitosis recognition in whole slide images of breast cancer tissue
S Çayır, G Solmaz, H Kusetogullari, F Tokat, E Bozaba, S Karakaya, ...
Neural Computing and Applications, 1-15, 2022
Whole slide histologic grading of breast cancer using convolutional neural networks.
G Demir, LO Iheme, G Solmaz, C Yazici, F Tokat, S Çayır, E Bozaba, ...
Journal of Clinical Oncology 40 (16_suppl), e13607-e13607, 2022
Impact Of Simulated Marginal Erosions of Volumetric Segmentation of Pancreatic Adenocarcinoma (PDA) on the Robustness of Radiomics Features
L Iheme, A Patra, G Suman, H Khasawneh, S Mukherjee, P Korfiatis, ...
ARRS 2022, 2022
Patch-Level Nuclear Pleomorphism Scoring Using Convolutional Neural Networks
LO Iheme, G Solmaz, F Tokat, S Çayir, E Bozaba, Ç Yazici, G Özsoy, ...
International Conference on Computer Analysis of Images and Patterns, 185-194, 2021
Nuclei Detection on Breast Cancer Histopathology Images Using RetinaNet
E Bozaba, G Solmaz, Ç Yazıcı, G Özsoy, F Tokat, LO Iheme, S Çayır, ...
2021 29th Signal Processing and Communications Applications Conference (SIU …, 2021
A Novel Semi-supervised Framework for Call Center Agent Malpractice Detection via Neural Feature Learning
Ş Ozan, LO Iheme
arXiv preprint arXiv:2106.02433, 2021
Machine Learning-based Silence Detection in Call Center Telephone Conversations
LO Iheme, Ş Ozan, E Akagündüz
2019 International Artificial Intelligence and Data Processing Symposium …, 2019
A Call for Automation, Standardization and Consistency in White Matter Hyperintensity Visual Grading
LO Iheme, M Kandemir, ZB Yalciner, D Unay
IEEE National Congress On Medical Technologies (TipTekno), 502-505, 2015
Automatic Grading of Periventricular White Matter Hyperintensities using FLAIR MRI
LO Iheme, SM Tepe, M Kandemir, T Kahraman, G Ünal, BZ Yalçıner, ...
ESMRMB 2012 Congress, 156-157, 2012
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Articles 1–20