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Pázmány Péter Catholic University

PPKE

Publications

15th Conference of the Hungarian Association for Image Analysis and Pattern Recognition (KÉPAF 2025) / 28-31 January 2025

PCD-VAE: A Permutation Invariant Point-Cloud Variational Auto-Encoder

Kövendi, J.
Benedek, Cs.
2024 IEEE 63rd Conference on Decision and Control (CDC) / 16-19 December 2024

Notes on Input Design: from Multi-Sine Design to Data-Driven Procedures

Gerencsér, L.
Michaletzky, Gy.
Bokor, J.
Polcz, P.
IEEE Control Systems Letters (Vol. 8) / 18 June 2024

Notes on Input Design: from Multi-Sine Design to Data-Driven Procedures

Gerencsér, L.
Michaletzky, Gy.
Bokor, J.
Polcz, P.
Image and Vision Computing

MVPCC-Net: multi-view based point cloud completion network for MLS data

Ibrahim, Y.
Benedek, Cs.
IET Control Theory & Applications (Vol. 17, Issue 8) / 12 January 2023

Efficient implementation of Gaussian process–based predictive control by quadratic programming

Polcz, P.
Péni, T.
Tóth, R.
International Conference on Pattern Recognition

Multi-view based 3D point cloud completion algorithm for vehicles

Ibrahim, Y.
Nagy, B.
Benedek, Cs.
European Signal Processing Conference (EUSIPCO)

Real-time vehicle localization and pose tracking in high-resolution 3D maps

Zováthi,Ö.
Pálffy. B.
Benedek, Cs.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022 / 30 May 2022

Real-time foreground segmentation for surveillance applications in NRCS lidar sequences

Kovács, L.
Kégl, M.
Benedek, Cs.
International Journal of Applied Earth Observation and Geoinformation

Point cloud registration and change detection in urban environment using an onboard Lidar sensor and MLS reference data

Zováthi,Ö.
Nagy, B.
Benedek, Cs.
Asilomar Conference on Signals, Systems & Computers

Real-time analysis of neuronal firing patterns via Hawkes processes

Gerencsér, L.
Perczel, Gy.
European Journal of Control

Lyapunov function computation for autonomous systems with complex dynamic behavior

Polcz, P.
Szederkényi, G.
Applied Sciences

Reconstruction of epidemiological data in Hungary using stochastic model predictive control

Polcz, P.
Csutak, B.
Szederkényi, G.

Pagination

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Kapcsolat

Prof. Dr. Péter Gáspár

H-1111 Budapest, Kende u. 13-17.

+36 1 279 6000

autonom@nemzetilabor.hu

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