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Alexander Reiterer

Geodät

Name	Alexander Reiterer
Ort	Österreich
Akademischer Grad bzw. Titel	Dipl.-Ing. Dr. techn.
Beruf	Geodät (charakteristischer Beruf) Wissenschaftlicher Mitarbeiter
Beziehung	Institut für Geodäsie und Geophysik (Wien). Forschungsgruppe Ingenieurgeodäsie
Weitere Angaben	Habil. Fach Angewandte Geodäsie an der TU München
Datensatztyp	Person
GND-Nummer	139978283
Datensatz-ID	139978283
Beteiligt an alle anzeigen Automated camera pose generation for high-resolution 3D reconstruction of bridges by unmanned aerial vehicles Automated inspection of complex engineering structures using robotics Conceptualization and first realization steps for a multi-camera system to capture tree streamlining in wind ECOSENSE - multi-scale quantification and modelling of spatio-temporal dynamics of ecosystem processes by smart autonomous sensor networks Image-based 3D reconstruction in laparoscopy: a review focusing on the quantitative evaluation by applying the reconstruction error Improving the efficiency of point cloud data management Mode coupling and signal energy distribution in an open-grown European beech tree Optical measurement system for monitoring railway infrastructure - a review Reducing training data using pre-trained foundation models: a case study on traffic sign segmentation using the segment anything model 3D reconstruction from 2D plans exemplified by bridge structures Automated method for SLAM evaluation in GNSS-denied areas Integrated gradients for feature assessment in point cloud-based data sets Methods and algorithms of an imaging total station Reconstructing geometrical models of indoor environments based on point clouds Semi-automatic 3D crack map generation and width evaluation for structural monitoring of reinforced concrete structures A study on the effect of multispectral LiDAR data on automated semantic segmentation of 3D-point clouds Fused projection-based point cloud segmentation Leitfaden zur optischen 3D-Messtechnik. Smart(sampling)augment: optimal and efficient data augmentation for semantic segmentation Leitfaden zur optischen 3D-Messtechnik Object semantic segmentation in point clouds - comparison of a deep learning and a knowledge-based method Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects Fully automated segmentation of 2D and 3D mobile mapping data for reliable modeling of surface structures using deep learning Novel observation concepts for image assisted total stations in applied geodesy : development steps and applications Second International Workshop on Application of Artificial Intelligence and Innovations in Engineering Geodesy (AIEG 2010) : Braunschweig (Germany), June 2010

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Katalog der Deutschen Nationalbibliothek

Alexander Reiterer

Automated camera pose generation for high-resolution 3D reconstruction of bridges by unmanned aerial vehicles

Automated inspection of complex engineering structures using robotics

Conceptualization and first realization steps for a multi-camera system to capture tree streamlining in wind

ECOSENSE - multi-scale quantification and modelling of spatio-temporal dynamics of ecosystem processes by smart autonomous sensor networks

Image-based 3D reconstruction in laparoscopy: a review focusing on the quantitative evaluation by applying the reconstruction error

Improving the efficiency of point cloud data management

Mode coupling and signal energy distribution in an open-grown European beech tree

Optical measurement system for monitoring railway infrastructure - a review

Reducing training data using pre-trained foundation models: a case study on traffic sign segmentation using the segment anything model

3D reconstruction from 2D plans exemplified by bridge structures

Automated method for SLAM evaluation in GNSS-denied areas

Integrated gradients for feature assessment in point cloud-based data sets

Methods and algorithms of an imaging total station

Reconstructing geometrical models of indoor environments based on point clouds

Semi-automatic 3D crack map generation and width evaluation for structural monitoring of reinforced concrete structures

A study on the effect of multispectral LiDAR data on automated semantic segmentation of 3D-point clouds

Fused projection-based point cloud segmentation

Leitfaden zur optischen 3D-Messtechnik.

Smart(sampling)augment: optimal and efficient data augmentation for semantic segmentation

Leitfaden zur optischen 3D-Messtechnik

Object semantic segmentation in point clouds - comparison of a deep learning and a knowledge-based method

Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects

Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects

Fully automated segmentation of 2D and 3D mobile mapping data for reliable modeling of surface structures using deep learning

Novel observation concepts for image assisted total stations in applied geodesy : development steps and applications

Second International Workshop on Application of Artificial Intelligence and Innovations in Engineering Geodesy (AIEG 2010) : Braunschweig (Germany), June 2010