Sütő József

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Informatikai Rendszerek és Hálózatok Tanszék

Egyetemi docens 2024-

Teljes publikációs lista

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Publikációs időszak:

2012-2024

2024

Sütő, J.: Improving the generalization capability of YOLOv5 on remote sensed insect trap images with data augmentation.
Multimed. Tools Appl. 83 (9), 27921-27934, 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Computer Networks and Communications (2023)

Q2 Hardware and Architecture (2023)

Q1 Media Technology (2023)

Q2 Software (2023)

Sütő, J.: Using Data Augmentation to Improve the Generalization Capability of an Object Detector on Remote-Sensed Insect Trap Images.
Sensors. 24 (14), 1-12, (cikkazonosító: 4502), 2024.

doi DEA

Folyóirat-mutatók:

Q1 Analytical Chemistry (2023)

Q1 Atomic and Molecular Physics, and Optics (2023)

Q2 Biochemistry (2023)

Q2 Electrical and Electronic Engineering (2023)

Q2 Information Systems (2023)

Q1 Instrumentation (2023)

Q2 Medicine (miscellaneous) (2023)

2023

Sütő, J.: Hardware and Software Support for Insect Pest Management.
Agriculture-Basel. 13 (9), 1-2, (cikkazonosító: 1818), 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Agronomy and Crop Science

Q2 Food Science

Q2 Plant Science

2022

Sütő, J.: An Improved Image Enhancement Method for Traffic Sign Detection.
Electronics (Switzerland). 11 (6), 1-13, (cikkazonosító: 871), 2022.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Computer Networks and Communications

Q2 Control and Systems Engineering

Q2 Hardware and Architecture

Q2 Electrical and Electronic Engineering

Q2 Signal Processing

Sütő, J.: A Novel Plug-in Board for Remote Insect Monitoring.
Agriculture-Basel. 12 (11), 1-16, 2022.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Agronomy and Crop Science

Q2 Food Science

Q2 Plant Science

Sütő, J.: Codling Moth Monitoring with Camera-Equipped Automated Traps: A Review.
Agriculture-Basel. 12 (10), 1721-, 2022.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Agronomy and Crop Science

Q2 Food Science

Q2 Plant Science

2021

Sütő, J.: Embedded System-Based Sticky Paper Trap with Deep Learning-Based Insect-Counting Algorithm.
Electronics (Switzerland). 10 (15), 1-13, 2021.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Computer Networks and Communications

Q2 Electrical and Electronic Engineering

Q2 Control and Systems Engineering

Q2 Hardware and Architecture

Q2 Signal Processing

Sütő, J.: Real-Time Lane Line Tracking Algorithm to Mini Vehicles.
Transp. Telecommun. 22 (4), 461-470, 2021.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q4 Computer Science Applications

Q3 Engineering (miscellaneous)

Sütő, J.: The effect of hyperparameter search on artificial neural network in human activity recognition.
Open Comp. Sci. 11 (1), 411-422, 2021.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Computer Science (miscellaneous)

2020

10.

Sütő, J., Oniga, I. L., Lung, C., Orha, I.: Comparison of offline and real-time human activity recognition results using machine learning techniques.
Neural Comput. Appl. 32 (20), 15673-15686, 2020.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Artificial Intelligence

Q1 Software

11.

Sütő, J., Jámbor, Z.: Music Stimuli Recognition from EEG Signals with EMOTIV EPOC Headset.
In: Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020). Ed.: by Gergely Kovásznai, István Fazekas, Tibor Tómács, CEUR, Eger, 309-317, 2020, (CEUR Worksh o p Proceedings, ISSN 1613-0073 ; 2650.)

DEA Scopus

12.

Sütő, J.: Plant leaf recognition with shallow and deep learning: a comprehensive study.
Intell. Data Anal. 24 (6), 1311-1328, 2020.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q4 Artificial Intelligence

Q3 Computer Vision and Pattern Recognition

Q4 Theoretical Computer Science

2019

13.

Sütő, J., Oniga, I. L.: Efficiency investigation from shallow to deep neural network techniques in human activity recognition.
Cogn. Syst. Res. 54, 37-49, 2019.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q3 Artificial Intelligence

Q3 Cognitive Neuroscience

Q3 Experimental and Cognitive Psychology

2018

14.

Sütő, J., Oniga, I. L.: Efficiency investigation of artificial neural networks in human activity recognition.
J. Ambient Intell. Humaniz. Comput. 9 (4), 1049-1060, 2018.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Computer Science (miscellaneous)

15.

Sütő, J., Oniga, I. L., Pop Sitar, P.: Music stimuli recognition from electroencephalogram signal with machine learning.
In: 2018 7th International Conference on Computers Communications and Control (ICCCC) : proceedings ISBN: 9781538619346

doi DEA

16.

Sütő, J., Oniga, I. L.: Music stimuli recognition in electroencephalogram signal.
Elektron. Elektrotech. 24 (4), 68-71, 2018.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q3 Electrical and Electronic Engineering

2017

17.

Sütő, J., Oniga, I. L., Pop-Sitar, P.: Feature analysis to human activity recognition.
Int. J. Comput. Commun. Control. 12 (1), 116-130, 2017.

DEA WoS Scopus

Folyóirat-mutatók:

Q3 Computational Theory and Mathematics

Q2 Computer Networks and Communications

Q3 Computer Science Applications

18.

Sütő, J., Oniga, I. L., Lung, C., Orha, I.: Recognition rate difference between real-time and offline human activity recognition.
In: Internet of Things for the Global Community : Proceedings : July 10-12, 2017, Madeira-Portugal / Fernando Morgado-Dias, IEEE, Danvers, 13-18, 2017. ISBN: 9781538620649

doi DEA

2016

19.

Oniga, I. L., Sütő, J.: Activity recognition in adaptive assistive systems using artificial neural networks.
Elektron. Elektrotech. 22 (1), 68-72, 2016.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Electrical and Electronic Engineering

20.

Sütő, J., Oniga, I. L., Pop Sitar, P.: Comparison of wrapper and filter feature selection algorithms on human activity recognition.
In: 2016 6th International Conference on Computers Communications & Control (ICCCC) : This edition of conference is dedicated to the 110th anniversary of Grigore C. Moisil (1906-1973) Romanian Mathematician, Computer Pioneer Award of IEEE Computer Society (1996 - posthumously). Eds.: I. Dzitac, F.G. Filip, M.J. Manolescu, IEEE, Piscataway, 124-129, 2016. ISBN: 9781509017355

doi DEA Scopus

2015

21.

Sütő, J., Oniga, I. L.: A new relation between "Twiddle Factors" in the fast Fourier transformation.
Elektron. Elektrotech. 21 (4), 56-59, 2015.

doi DEA

Folyóirat-mutatók:

Q2 Electrical and Electronic Engineering

22.

Oniga, I. L., Sütő, J.: Optimal recognition method of human activities using artificial neural networks.
Meas. Sci. Rev. 15 (6), 323-327, 2015.

doi DEA

Folyóirat-mutatók:

Q3 Biomedical Engineering

Q2 Control and Systems Engineering

Q3 Instrumentation

23.

Sütő, J., Oniga, I. L., Buchman, A.: Real time human activity monitoring.
Ann. Math. et Inf. 44, 187-196, 2015.

DEA

Folyóirat-mutatók:

Q4 Computer Science (miscellaneous)

Q4 Mathematics (miscellaneous)

2014

24.

Sütő, J., Oniga, I. L., Hegyesi, G.: A simple fast Fourier transformation algorithm to microcontrollers and mini computers.
In: 18th International Conference on Intelligent Engineering Systems (INES), 2014 : proceedings. Ed.: A. Szakal, IEEE, [Pistacaway], 61-65, 2014. ISBN: 9781479946150

doi DEA

25.

Oniga, I. L., Sütő, J.: Human activity recognition using neural networks.
In: Proceedings of the 2014 15th International Carpathian Control Conference (ICCC). Ed.: Ivo Petrás, Igor Podlubny, Ján Kacur, Radim Farana, IEEE, Piscataway, 403-406, 2014. ISBN: 9781479935284

doi DEA