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Browsing by Subject "Classification (of information)"

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Active feature acquisition for opinion stream classification under drift

Shivakumaraswamy, Ranjith; Beyer, Christian; Unnikrishnan, Vishnu; Ntoutsi, Eirini; Spiliopoulou, Myra (Aachen, Germany : RWTH Aachen, 2019)

Active stream learning is frequently used to acquire labels for instances and less frequently to determine which features should be considered as the stream evolves. We introduce a framework for active feature selection, ...
An optical-flow-based monitoring method for measuring translational motion in infrared-thermographic images of AFP processes

Denkena, Berend; Schmidt, Carsten; Timmermann, Marc; Friedel, Andreas (Berlin : Springer, 2022)

This paper presents a novel method for a precise localization of the automated-fiber-placement head, without the need for a data access to the machine control. It is based on a sub-pixel accurate optical-flow-algorithm ...
Automatic classification of aerial imagery for urban hydrological applications

Paul, A.; Yang, C.; Breitkopf, U.; Liu, Y.; Wang, Z.; Rottensteiner, F.; Wallner, M.; Verworn, A.; Heipke, C. (Göttingen : Copernicus GmbH, 2018)

In this paper we investigate the potential of automatic supervised classification for urban hydrological applications. In particular, we contribute to runoff simulations using hydrodynamic urban drainage models. In order ...
Automatic classification of high resolution satellite imagery - A case study for urban areas in the Kingdom of Saudi Arabia

Maas, Alina; Alrajhi, M.; Alobeid, A.; Heipke, Christian (Göttingen : Copernicus GmbH, 2017)

Updating topographic geospatial databases is often performed based on current remotely sensed images. To automatically extract the object information (labels) from the images, supervised classifiers are being employed. ...
A comparison of two strategies for avoiding negative transfer in domain adaptation based on logistic regression

Paul, A.; Vogt, K.; Rottensteiner, F.; Ostermann, J.; Heipke, C. (Göttingen : Copernicus GmbH, 2018)

In this paper we deal with the problem of measuring the similarity between training and tests datasets in the context of transfer learning (TL) for image classification. TL tries to transfer knowledge from a source domain, ...
Contextual land use classification: How detailed can the class structure be?

Albert, Lena; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2016)

The goal of this paper is to investigate the maximum level of semantic resolution that can be achieved in an automated land use change detection process based on mono-temporal, multi-spectral, high-resolution aerial image ...
The contribution of gis and remote sensing in urban land use negotiation in developing countries

Karanja, Faith; Lohmann, Peter ([Wechselnde Verlagsorte] : ISPRS, 2000)

Most of the studies related to urban environments in developing countries focus mainly on particular aspects e.g.communication, residential, vegetated areas, etc. However, planners who are concerned about urban space ...
A dynamic Bayes Network for visual pedestrian tracking

Klinger, Tobias; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2014)

Many tracking systems rely on independent single frame detections that are handled as observations in a recursive estimation framework. If these observations are imprecise the generated trajectory is prone to be updated ...
Estimation of biomass potential based on classification and height information

Müller, S.; Büscher, O.; Jandewerth, M. (Göttingen : Copernicus GmbH, 2013)

On the way to make energy supply independent from fossil resources more and more renewable energy sources have to be explored. Biomass has become an important energy resource during the last years and the consumption is ...
Hierarchical higher order crf for the classification of airborne lidar point clouds in urban areas

Niemeyer, Joachim; Rottensteiner, Franz; Sörgel, Uwe; Heipke, Christian (Göttingen : Copernicus GmbH, 2016)

We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point ...
Improved classification of satellite imagery using spatial feature maps extracted from social media

Leichter, Artem; Wittich, Dennis; Rottensteiner, Franz; Werner, Martin; Sester, Monika (Katlenburg-Lindau : Copernicus Publications, 2018)

In this work, we consider the exploitation of social media data in the context of Remote Sensing and Spatial Information Sciences. To this end, we explore a way of augmenting and integrating information represented by ...
Joint classification of ALS and DIM point clouds

Politz, F.; Sester, M. (Göttingen : Copernicus GmbH, 2019)

National mapping agencies (NMAs) have to acquire nation-wide Digital Terrain Models on a regular basis as part of their obligations to provide up-to-date data. Point clouds from Airborne Laser Scanning (ALS) are an important ...
Monitoring concepts for coastal areas using lidar data

Schmidt, Alena; Rottensteiner, Franz; Sörgel, Uwe (Göttingen : Copernicus GmbH, 2013)

Coastal areas are characterized by high spatial and temporal variability. In order to detect undesired changes at early stages, enabling rapid countermeasures to mitigate or minimize potential harm or hazard, a recurrent ...
Multi-source hierarchical conditional random field model for feature fusion of remote sensing images and LiDAR data

Zhang, Z.; Yang, M.Y.; Zhoua, M. (Katlenburg-Lindau : Copernicus Publications, 2013)

Feature fusion of remote sensing images and LiDAR points cloud data, which have strong complementarity, can effectively play the advantages of multi-class features to provide more reliable information support for the remote ...
Multi-task deep learning with incomplete training samples for the image-based prediction of variables describing silk fabrics

Dorozynski, M.; Clermont, D.; Rottensteiner, F. (Göttingen : Copernicus GmbH, 2019)

This paper presents a method for the classification of images of silk fabrics with the aim to predict properties such as the placeand time of origin and the production technique. The proposed method was developed in the ...
Multiple-model based verification of japanese road data

Ziems, M.; Fujimura, H.; Heipke, Christian; Rottensteiner, Franz (Göttingen : Copernicus GmbH, 2010)

This paper describes a semi-automatic system for road verification from high resolution orthophotos in an urban context. The system combines several road detection and road verification approaches from current literature ...
Multitemporal interpretation of remote sensing data

Müller, Sönke; Mota, Guilherme Lucio Abelha; Liedtke, Claus-Eberhard (London : International Society for Photogrammetry and Remote Sensing, 2004)

The automated interpretation of aerial image data is a task with increasing significance for several applications, e.g. quality control and automatic updating of GIS data, automatic land use change detection, measurement ...
Semiautomatic quality control of topographic reference datasets

Becker, Christian; Breitkopf, Uwe; Büschenfeld, Torsten; Busch, A.; Grünreich, D.; Heipke, Christian; Helmholz, Petra; Müller, S.; Ostermann, Jörn; Pahl, M.; Vogt, Karsten; Ziems, M. (Göttingen : Copernicus GmbH, 2010)

The usefulness and acceptance of spatial information systems are mainly dependent on the quality of the underlying geodata. This paper describes a system for semiautomatic quality control of existing geospatial data via ...
The STEM-ECR Dataset: Grounding Scientific Entity References in STEM Scholarly Content to Authoritative Encyclopedic and Lexicographic Sources

D'Souza, Jennifer; Hoppe, Anett; Brack, Arthur; Jaradeh, Mohamad Yaser; Auer, Sören; Ewerth, Ralph (Paris : The European Language Resources Association (ELRA), 2020)

We introduce the STEM (Science, Technology, Engineering, and Medicine) Dataset for Scientific Entity Extraction, Classification, and Resolution, version 1.0 (STEM-ECR v1.0). The STEM-ECR v1.0 dataset has been developed to ...
Supporting contextualized information finding with automatic excerpt categorization

Kawase, Ricardo; Siehndel, Patrick; Pereira Nunes, Bernardo (Amsterdam [u.a.] : Elsevier, 2014)

The volume of information on the Web is constantly growing. Consequently, finding specific pieces of information becomes a harder task. Wikipedia, the largest online reference Website is beginning to witness this phenomenon. ...

Now showing items 1-20 of 23

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Browsing by Subject "Classification (of information)"

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