Content for tag Deep Learning:

Publications - 33

HIDRA-D: deep-learning model for dense sea level forecasting using sparse altimetry and tide gauge data

Marko Rus, Matjaž Ličer and Matej Kristan

Geoscientific Model Development, Copernicus Publications, 2026
Vision-Based 6-DoF Grasp Pose Estimation for Robot Cloth Unfolding

Domen Tabernik, Peter Nimac, Jan Jerićević, Danijel Skočaj and Andrej Gams

IEEE Transactions on Cybernetics, IEEE, 2026
Application of the HIDRA2 deep-learning model for sea level forecasting along the Estonian coast of the Baltic Sea

Amirhossein Barzandeh, Matjaž Ličer, Marko Rus, Matej Kristan, Ilja Maljutenko, Jüri Elken, Priidik Lagemaa and Rivo Uiboupin

Ocean Science, 2025
CRITER 1.0: a coarse reconstruction with iterative refinement network for sparse spatio-temporal satellite data

Matjaž Zupančič Muc, Vitjan Zavrtanik, Alex Barth, Aida Alvera-Azcarate, Matjaž Ličer and Matej Kristan

Geoscientific Model Development, Copernicus Publications, 2025
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures

Marko Rus, Hrvoje Mihanović, Matjaž Ličer and Matej Kristan

Geoscientific Model Development, Copernicus Publications, 2025
Center Direction Network for Grasping Point Localization on Cloths

Domen Tabernik, Jon Muhovič, Matej Urbas and Danijel Skočaj

IEEE Robotics and Automation Letters, IEEE, 2024
Dense Center-Direction Regression for Object Counting and Localization with Point Supervision

Domen Tabernik, Jon Muhovič and Danijel Skočaj

Pattern Recognition, 2024
HIDRA3: A Robust Deep-Learning Model for Multi-Point Sea-Surface Height and Storm Surges Forecasting

Marko Rus, Hrvoje Mihanović, Matjaž Ličer and Matej Kristan

55th International Liège Colloquium on Ocean Dynamics, 2024
HIDRA3: A Robust Deep-Learning Model for Multi-Point Sea-Surface Height Forecasting

Marko Rus, Hrvoje Mihanović, Matjaž Ličer and Matej Kristan

EGU General Assembly 2024, 2024
SuperSimpleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect Detection

Blaž Rolih, Matic Fučka and Danijel Skočaj

Pattern Recognition: 27th International Conference, ICPR 2024, Springer, 2024
Towards the deep learning recognition of cultivated terraces based on Lidar data: The case of Slovenia

Rok Ciglič, Anže Glušič, Lenart Štaut and Luka Čehovin Zajc

Moravian Geographical Reports, 2024
3D-model-based Rendering of Synthetic Images For Training Segmentation Models in an Industrial Environment

Matic Fučka, Marko Rus, Jakob Božič and Danijel Skočaj

ROSUS 2023 - Računalniška obdelava slik in njena uporaba v Sloveniji 2023, 2023
Automated detection and segmentation of cracks in concrete surfaces using joined segmentation and classification deep neural network

Domen Tabernik, Matic Šuc and Danijel Skočaj

Construction and Building Materials, 2023
Deep-learning transformer-based sea level modeling ensemble for the Adriatic basin

Marko Rus, Matej Kristan and Matjaž Ličer

54th International Liège Colloquium on Ocean Dynamics, 2023
Diskriminativna metoda za detekcijo 3D anomalij

Vitjan Zavrtanik, Matej Kristan and Danijel Skočaj

ERK, 2023
HIDRA-T – A Transformer-Based Sea Level Forecasting Method

Marko Rus, Anja Fettich, Matej Kristan and Matjaž Ličer

International Electrotechnical and Computer Science Conference (ERK), 2023
HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic

Marko Rus, Anja Fettich, Matej Kristan and Matjaž Ličer

EGU General Assembly 2023, 2023
HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic

Marko Rus, Anja Fettich, Matej Kristan and Matjaž Ličer

Geoscientific Model Development, Copernicus Publications, 2023
Lokalizacija in ocenjevanje lege predmeta v treh prostostnih stopnjah s središčnimi smernimi vektorji

Domen Tabernik, Jon Muhovič and Danijel Skočaj

ERK, 2023
Improvements of the Adriatic Deep-Learning Sea Level Modeling Network HIDRA

Marko Rus, Matjaž Ličer and Matej Kristan

MAELSTROM dissemination workshop, 2022
Video-Based Ski Jump Style Scoring from Pose Trajectory

Dejan Štepec and Danijel Skočaj

IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), 2022
Analiza robustnosti globokih nenadzorovanih metod za detekcijo vizualnih anomalij

Jakob Božič, Vitjan Zavrtanik and Danijel Skočaj

ERK, 2021
Deep reinforcement learning for map-less goal-driven robot navigation

Matej Dobrevski and Danijel Skočaj

International Journal of Advanced Robotic Systems, 2021
Fully supervised and point-supervised ship detection using center prediction, LUVSS-2021-11

Domen Tabernik, Jon Muhovič and Danijel Skočaj

Technical Report, 2021
HIDRA 1.0: deep-learning-based ensemble sea level forecasting in the northern Adriatic

Lojze Žust, Anja Fettich, Matej Kristan and Matjaž Ličer

Geoscientific Model Development, Copernicus Publications, 2021
Mixed supervision for surface-defect detection: from weakly to fully supervised learning

Jakob Božič, Domen Tabernik and Danijel Skočaj

Computers in Industry, Elsevier, 2021
Adaptive Dynamic Window Approach for Local Navigation

Matej Dobrevski and Danijel Skočaj

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2020
End-to-end training of a two-stage neural network for defect detection

Jakob Božič, Domen Tabernik and Danijel Skočaj

ICPR, 2020
O klasifikaciji slik v ne-enolično določljive razrede

Jon Muhovič, Domen Tabernik and Danijel Skočaj

ERK, 2020
Segmentation-Based Deep-Learning Approach for Surface-Defect Detection

Domen Tabernik, Samo Šela, Jure Skvarč and Danijel Skočaj

Journal of Intelligent Manufacturing, 2020
Deep Learning for Large-Scale Traffic-Sign Detection and Recognition

Domen Tabernik and Danijel Skočaj

Transactions on Intelligent Transportation Systems, IEEE, 2019
Deep-learning-based computer vision system for surface-defect detection

Domen Tabernik, Samo Šela, Jure Skvarč and Danijel Skočaj

Proceedings of the 12th International Conference on Computer Vision Systems, 2019
Towards large-scale traffic sign detection and recognition

Peter Uršič, Domen Tabernik, Rok Mandeljc and Danijel Skočaj

Proceedings of the 22nd Computer Vision Winter Workshop, 2017

Applications - 1

ViCoS Cube

Modular application code for the ViCoS demonstration cell, together with links to the associated ROSUS 2024 paper.

Libraries - 1

PixelPipes

Infinite data streams for deep learning.