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2020 – today
- 2024
[j12]Modafar Al-Shouha
, Gábor Szücs:
Single and Combined Algorithms for Open Set Classification on Image Datasets. Acta Cybern. 26(3): 297-322 (2024)- [j11]Gábor Szücs, Rego Borsodi, Dávid Papp:
Multi-camera trajectory matching based on hierarchical clustering and constraints. Multim. Tools Appl. 83(15): 44879-44902 (2024) - [j10]Longjian Wang, Shuichao Zhang, Gábor Szücs, Yonggang Wang:
Identifying the critical nodes in multi-modal transportation network with a traffic demand-based computational method. Reliab. Eng. Syst. Saf. 244: 109956 (2024) - 2023
- [j9]Gábor Szücs, Richárd Kiss:
2N labeling defense method against adversarial attacks by filtering and extended class label set. Multim. Tools Appl. 82(11): 16717-16740 (2023) - [j8]Gábor Szücs:
Multiclass classification by Min-Max ECOC with Hamming distance optimization. Vis. Comput. 39(9): 3949-3961 (2023) - [c23]Modafar Al-Shouha, Gábor Szücs:
iPIC-XAI: Improving PIC-XAI for Enhanced Image Captioning Explanation. CogInfoCom 2023: 45-50 - [c22]Levente Rácz, Dávid Szabó, Gábor Göcsei, Tamás Mátrai, Bálint Németh, Gábor Szücs:
Field Experience on a Dynamic Line Rating System's Costs and Benefits. IAS 2023: 1-5 - [c21]Modafar Al-Shouha, Gábor Szücs:
PIC-XAI: Post-hoc Image Captioning Explanation using Segmentation. SACI 2023: 33-38 - [c20]Dávid Maruscsák, Gábor Szücs, Jeanne Vézien, Christian Sandor:
MiniGI: Guerilla Mappings in Miniature. SIGGRAPH Asia XR 2023: 18:1 - [c19]Balázs Fodor, Ákos Jakub, Gábor Szücs, Balázs Sonkoly:
A Multi-Agent Deep-Reinforcement Learning Approach for Application-Agnostic Microservice Scaling. VCC 2023: 139-144 - 2022
- [j7]Gábor Szücs, Dávid Papp:
Zero Initialised Unsupervised Active Learning by Optimally Balanced Entropy-Based Sampling for Imbalanced Problems. J. Exp. Theor. Artif. Intell. 34(5): 781-814 (2022) - [c18]Marcell Németh, Gábor Szücs:
Split Feature Space Ensemble Method using Deep Reinforcement Learning for Algorithmic Trading. ICCTA 2022: 188-194 - [c17]Gábor Szücs, Modafar Al-Shouha:
Modular StoryGAN with Background and Theme Awareness for Story Visualization. ICPRAI (1) 2022: 275-286
2010 – 2019
- 2019
- [j6]Jaroslav Budis, Juraj Gazdarica, Ján Radvánszky, Gábor Szücs, Marcel Kucharík, Lucia Strieskova, Iveta Gazdaricova, Maria Harsanyova, Frantisek Duris, Gabriel Minarik, Martina Sekelska, Bálint Nagy, Ján Turna, Tomás Szemes:
Combining count- and length-based z-scores leads to improved predictions in non-invasive prenatal testing. Bioinform. 35(8): 1284-1291 (2019) - [c16]Dávid Papp, Gábor Szücs, Zsolt Knoll:
Machine preparation for human labelling of hierarchical train sets by spectral clustering. CogInfoCom 2019: 157-162 - [c15]Dávid Papp, Gábor Szücs, Zsolt Knoll:
Difference based query strategies in active learning. SISY 2019: 35-40 - [c14]Gábor Szücs, Dorottya Huszti:
Seq2seq Deep Learning Method for Summary Generation by LSTM with Two-way Encoder and Beam Search Decoder. SISY 2019: 221-226 - 2018
- [j5]Gábor Szücs, Bence Tamás:
Body Part Extraction and Pose Estimation Method in Rowing Videos. J. Comput. Inf. Technol. 26(1): 29-43 (2018) - [j4]Dávid Papp, Gábor Szücs:
Double Probability Model for Open Set Problem at Image Classification. Informatica 29(2): 353-369 (2018) - [c13]Dávid Papp, Gábor Szücs:
Extended Margin and Soft Balanced Strategies in Active Learning. ADBIS 2018: 69-81 - 2017
- [j3]Dávid Papp, Gábor Szücs:
Balanced Active Learning Method for Image Classification. Acta Cybern. 23(2): 645-658 (2017) - [c12]Dávid Papp, Ferenc Mogyorósi, Gábor Szücs:
Image Matching for Individual Recognition with SIFT, RANSAC and MCL. CLEF (Working Notes) 2017 - 2016
- [c11]Dávid Papp, Dániel Lovas, Gábor Szücs:
Object Detection, Classification, Tracking and individual Recognition for Sea Images and Videos. CLEF (Working Notes) 2016: 525-533 - [c10]Bálint Pál Tóth, Márton József Tóth, Dávid Papp, Gábor Szücs:
Deep Learning and SVM Classification for Plant Recognition in Content-Based Large Scale Image Retrieval. CLEF (Working Notes) 2016: 569-578 - 2015
- [c9]Gábor Szücs, Dávid Papp, Dániel Lovas:
SVM classification of moving objects tracked by Kalman filter and Hungarian method. CLEF (Working Notes) 2015 - 2014
- [c8]Gábor Szücs, Dávid Papp, Dániel Lovas:
Viewpoints Combined Classification Method in Image-based Plant Identification Task. CLEF (Working Notes) 2014: 763-770 - [c7]Zsombor Paroczi, Bálint Fodor, Gábor Szücs:
Re-Ranking the Image Search Results for Relevance and Diversity in MediaEval 2014 Challenge. MediaEval 2014 - [c6]Zsombor Paroczi, Bálint Fodor, Gábor Szücs:
DCLab at MediaEval2014 Search and Hyperlinking Task. MediaEval 2014 - 2013
- [j2]Gábor Szücs:
Random Response Forest for Privacy-Preserving Classification. J. Comput. Eng. 2013: 397096:1-397096:6 (2013) - [c5]Gábor Szücs:
Hierarchical image browsing based on visual information. CogInfoCom 2013: 97-102 - [c4]Gábor Szücs, Zsombor Paroczi, Dániel Máté Vincz:
BMEMTM at MediaEval 2013 Retrieving Diverse Social Images Task: Analysis of Text and Visual Information. MediaEval 2013 - 2012
- [c3]László Dudás, Zsolt Fekete, Julianna Göbölös-Szabó, A. Radnai, A. Salanki, A. Szabo, Gábor Szücs:
OWLAP - Using OLAP approach in anomaly detection: Award: Good support for the data preparation, analysis, and presentation process. IEEE VAST 2012: 267-268 - 2011
- [j1]Gábor Szücs:
Equilibrium estimation based on unreliable information in transport networks by adaptive simulation. Int. J. Adv. Intell. Paradigms 3(3/4): 273-285 (2011) - [c2]Norbert Bánfi, László Dudás, Zsolt Fekete, Julianna Göbölös-Szabó, András Lukács, Ádám Nagy, Adrienn Szabó, Zoltán Szabó, Gábor Szücs:
City sentinel - VAST 2011 mini challenge 1 award: "Outstanding integration of computational and visual methods". IEEE VAST 2011: 305-306 - 2010
- [c1]András Ferenc Kovács, Gábor Magyar, Gábor Szücs:
Collaborative Media Content Management. ISD 2010: 469-478
Coauthor Index
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last updated on 2024-10-07 22:14 CEST by the dblp team
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