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Balázs Harangi
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- affiliation: University of Debrecen, Hungary
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2020 – today
- 2024
- [j10]Robert Lakatos
, Gergo Bogacsovics, Balázs Harangi
A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews. Big Data Cogn. Comput. 8(3): 20 (2024) - [j9]Tamás Katona
Advanced Multi-Label Image Classification Techniques Using Ensemble Methods. Mach. Learn. Knowl. Extr. 6(2): 1281-1297 (2024) - [j8]Mokhaled N. A. Al-Hamadani
Reinforcement Learning Algorithms and Applications in Healthcare and Robotics: A Comprehensive and Systematic Review. Sensors 24(8): 2461 (2024) - [j7]Norbert Serban
Distinguishing the Uterine Artery, the Ureter, and Nerves in Laparoscopic Surgical Images Using Ensembles of Binary Semantic Segmentation Networks. Sensors 24(9): 2926 (2024) - 2023
- [c32]Gergo Bogacsovics, Balázs Harangi, András Hajdu:
Increasing the diversity of ensemble members for accurate brain tumor classification. CBMS 2023: 529-534 - [c31]Norbert Serban, Balázs Harangi:
Localization-Enhanced Voting-based Ensemble of Semantic Segmentation Models for Cervical Polyp Segmentation. CBMS 2023: 712-715 - [c30]Arpad Pandy, Balázs Harangi, András Hajdu:
Extracting Drug Names from Medical Reports. CSIT 2023: 1-4 - [c29]Arpad Pandy, Balázs Harangi, András Hajdu:
Extracting Drug Names From Medical Reports. CSIT 2023: 1-4 - [i2]Robert Lakatos, Gergo Bogacsovics, Balázs Harangi, István Lakatos, Attila Tiba, János Tóth, Marianna Szabo, András Hajdu:
A Cloud-based Machine Learning Pipeline for the Efficient Extraction of Insights from Customer Reviews. CoRR abs/2306.07786 (2023) - 2022
- [j6]Gergo Bogacsovics, János Tóth, András Hajdu, Balázs Harangi:
Enhancing CNNs through the use of hand-crafted features in automated fundus image classification. Biomed. Signal Process. Control. 76: 103685 (2022) - [c28]David Kupas, Balázs Harangi:
Classification of Pap-smear cell images using deep convolutional neural network accelerated by hand-crafted features. EMBC 2022: 1452-1455 - 2021
- [c27]David Kupas, Balázs Harangi:
Solving the problem of imbalanced dataset with synthetic image generation for cell classification using deep learning. EMBC 2021: 2981-2984 - [c26]István Lakatos, András Hajdu, Balázs Harangi:
Molecule Classification Using Visualization and Convolutional Neural Network. ISBI 2021: 1695-1698 - 2020
- [j5]Balázs Harangi, Agnes Baran, András Hajdu:
Assisted deep learning framework for multi-class skin lesion classification considering a binary classification support. Biomed. Signal Process. Control. 62: 102041 (2020)
2010 – 2019
- 2019
- [c25]Balázs Harangi, János Tóth, Agnes Baran, András Hajdu:
Automatic screening of fundus images using a combination of convolutional neural network and hand-crafted features. EMBC 2019: 2699-2702 - [c24]Balázs Harangi, János Tóth, Gergo Bogacsovics, David Kupas, Laszlo Kovacs, András Hajdu:
Cell detection on digitized Pap smear images using ensemble of conventional image processing and deep learning techniques. ISPA 2019: 38-42 - [c23]János Tóth, Tibor Péter Kapusi, Balázs Harangi, Henrietta Tomán, András Hajdu:
Accelerating the Optimization of a Segmentation Ensemble using Image Pyramids. ISPA 2019: 43-48 - [c22]David Kupas, Peter Torok, András Hajdu, Balázs Harangi:
Visualization of Fibroid in Laparoscopy Videos using Ultrasound Image Segmentation and Augmented Reality. ISPA 2019: 60-63 - 2018
- [j4]Balázs Harangi
Skin lesion classification with ensembles of deep convolutional neural networks. J. Biomed. Informatics 86: 25-32 (2018) - [c21]Péter Burai, András Hajdu
Segmentation of the uterine wall by an ensemble of fully convolutional neural networks. EMBC 2018: 49-52 - [c20]Balázs Harangi, Agnes Baran, András Hajdu
Classification Of Skin Lesions Using An Ensemble Of Deep Neural Networks. EMBC 2018: 2575-2578 - [c19]Balázs Harangi, János Tóth, András Hajdu
Fusion of Deep Convolutional Neural Networks for Microaneurysm Detection in Color Fundus Images. EMBC 2018: 3705-3708 - 2017
- [c18]Melinda Pap, Balázs Harangi, András Hajdu
Automatic Pigment Network Classification Using a Combination of Classical Texture Descriptors and CNN Features. CBMS 2017: 343-348 - [c17]Balázs Harangi, András Hajdu
Recognizing Ureter and Uterine Artery in Endoscopic Images Using a Convolutional Neural Network. CBMS 2017: 726-727 - [c16]David Kupas, Balázs Harangi, Gyorgy Czifra, Gabor Andrassy:
Decision support system for the diagnosis of neurological disorders based on gaze tracking. ISPA 2017: 37-40 - [c15]Balázs Harangi, András Hajdu
Differentiating ureter and arteries in the pelvic via endoscope using deep neural network. ISPA 2017: 86-89 - [c14]Attila Tiba
Efficient texture regularity estimation for second order statistical descriptors. ISPA 2017: 90-94 - [c13]Péter Burai, Balázs Harangi:
Pixelwise segmentation of uterine wall in endoscopic video frame using convolutional neural networks. ISPA 2017: 95-98 - [i1]Balázs Harangi:
Skin lesion detection based on an ensemble of deep convolutional neural network. CoRR abs/1705.03360 (2017) - 2016
- [c12]András Hajdu
Measuring regularity of network patterns by grid approximations using the LLL algorithm. ICPR 2016: 1524-1529 - 2015
- [b1]Balázs Harangi:
Single/Multiple Object Detection Problems in Medical Image Analyses. University of Debrecen, Hungary, 2015 - [j3]Balázs Harangi
Detection of the optic disc in fundus images by combining probability models. Comput. Biol. Medicine 65: 10-24 (2015) - [c11]János Tóth, Lorant Bartha, Tamás Szabó, István Lázár, Balázs Harangi, András Hajdu
An online application for storing, analyzing, and sharing dermatological data. CogInfoCom 2015: 339-342 - [c10]Renátó Besenczi, Kristóf Szitha, Balázs Harangi, Adrienne Csutak, András Hajdu
Automatic optic disc and optic cup detection in retinal images acquired by mobile phone. ISPA 2015: 193-198 - 2014
- [j2]Balázs Harangi
Automatic exudate detection by fusing multiple active contours and regionwise classification. Comput. Biol. Medicine 54: 156-171 (2014) - [c9]János Tóth, Laszlo Kovacs, Balázs Harangi, Csaba Kiss, Andras Mohacsi, Zoltan Orosz, András Hajdu
An online benchmark system for image processing algorithms. CogInfoCom 2014: 377-382 - [c8]János Tóth, Laszlo Kovacs, Balázs Harangi, Csaba Kiss, Andras Mohacsi, Zoltan Orosz, András Hajdu
An online system for algorithm benchmarking. CogInfoCom 2014: 383 - [c7]Balázs Harangi, András Hajdu
Detection of exudates in fundus images using a Markovian segmentation model. EMBC 2014: 130-133 - 2013
- [c6]Balázs Harangi
Improving automatic exudate detection based on the fusion of the results of multiple active contours. ISBI 2013: 45-48 - 2012
- [j1]Rashid Jalal Qureshi, Laszlo Kovacs, Balázs Harangi
Combining algorithms for automatic detection of optic disc and macula in fundus images. Comput. Vis. Image Underst. 116(1): 138-145 (2012) - [c5]Balázs Harangi
Automatic exudate detection with improved Naïve-Bayes classifier. CBMS 2012: 1-4 - [c4]Balázs Harangi
Automatic exudate detection using active contour model and regionwise classification. EMBC 2012: 5951-5954 - [c3]Balázs Harangi
Improving the accuracy of optic disc detection by finding maximal weighted clique of multiple candidates of individual detectors. ISBI 2012: 602-605 - 2011
- [c2]Brigitta Nagy, Balázs Harangi, Bálint Antal, András Hajdu:
Ensemble-based exudate detection in color fundus images. ISPA 2011: 700-703 - 2010
- [c1]Balázs Harangi
Automatic detection of the optic disc using majority voting in a collection of optic disc detectors. ISBI 2010: 1329-1332
Coauthor Index
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last updated on 2024-12-26 01:55 CET by the dblp team
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