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Alexandros Gkillas
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2020 – today
- 2024
- [j3]Alexandros Gkillas
, Aris S. Lalos
, Evangelos K. Markakis
, Ilias Politis
:
A Federated Deep Unrolling Method for Lidar Super-Resolution: Benefits in SLAM. IEEE Trans. Intell. Veh. 9(1): 199-215 (2024) - 2023
- [j2]Alexandros Gkillas, Dimitrios I. Kosmopoulos, Kostas Berberidis:
Cost-efficient coupled learning methods for recovering near-infrared information from RGB signals: Application in precision agriculture. Comput. Electron. Agric. 209: 107833 (2023) - [j1]Alexandros Gkillas
, Dimitris Ampeliotis
, Kostas Berberidis
:
Connections Between Deep Equilibrium and Sparse Representation Models With Application to Hyperspectral Image Denoising. IEEE Trans. Image Process. 32: 1513-1528 (2023) - [c13]Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis:
Deep Equilibrium Models Meet Federated Learning. EUSIPCO 2023: 1873-1877 - [c12]Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis:
A Highly Interpretable Deep Equilibrium Network for Hyperspectral Image Deconvolution. ICASSP 2023: 1-5 - [c11]Dimitris Ampeliotis, Alexandros Gkillas:
Subspace Parsimonious Dictionary Learning and its use in Federated Learning. DSP 2023: 1-5 - [c10]Christos Anagnostopoulos, Alexandros Gkillas, Nikos Piperigkos
, Aris S. Lalos:
Federated Deep Feature Extraction-based SLAM for Autonomous Vehicles. DSP 2023: 1-5 - [c9]Alexandros Gkillas, Gerasimos Arvanitis, Aris S. Lalos, Konstantinos Moustakas:
Federated Learning for Lidar Super Resolution on Automotive Scenes. DSP 2023: 1-5 - [c8]Alexandros Gkillas, Aris S. Lalos:
Resource Efficient Federated Learning for Deep Anomaly Detection in Industrial IoT applications. DSP 2023: 1-5 - [c7]Alexandros Gkillas, Aris S. Lalos, Dimitris Ampeliotis:
An Efficient Deep Unrolling Super-Resolution Network for Lidar Automotive Scenes. ICIP 2023: 1840-1844 - [c6]Alexandros Gkillas, Christos Anagnostopoulos, Aris S. Lalos:
Deep Federated Unrolling for Boosting Low-Resolution Lidar-Based SLAM Solutions. MMSP 2023: 1 - [i4]Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis:
Deep Equilibrium Models Meet Federated Learning. CoRR abs/2305.18646 (2023) - [i3]Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis:
An Optimization-based Deep Equilibrium Model for Hyperspectral Image Deconvolution with Convergence Guarantees. CoRR abs/2306.06378 (2023) - 2022
- [c5]Alexandros Gkillas, Aris S. Lalos:
Missing Data Imputation for Multivariate Time series in Industrial IoT: A Federated Learning Approach. INDIN 2022: 87-94 - [c4]Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis:
Federated Dictionary Learning from Non-IID Data. IVMSP 2022: 1-5 - [i2]Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis:
Deep Equilibrium Assisted Block Sparse Coding of Inter-dependent Signals: Application to Hyperspectral Imaging. CoRR abs/2203.15901 (2022) - 2021
- [c3]Alexandros Gkillas, Dimitrios I. Kosmopoulos
, Constantinos Constantinopoulos, Dimitris Ampeliotis, Kostas Berberidis:
A Method for Recovering Near Infrared Information from RGB Measurements with Application in Precision Agriculture. EUSIPCO 2021: 616-620 - [i1]Alexandros Gkillas, Dimitrios I. Kosmopoulos:
A cross-domain recommender system using deep coupled autoencoders. CoRR abs/2112.07617 (2021) - 2020
- [c2]Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis:
Fast Sparse Coding Algorithms for Piece-wise Smooth Signals. EUSIPCO 2020: 2040-2044 - [c1]Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis:
Efficient Coupled Dictionary Learning And Sparse Coding For Noisy Piecewise-Smooth Signals: Application To Hyperspectral Imaging. ICIP 2020: 231-235
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last updated on 2024-04-25 05:53 CEST by the dblp team
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