Daniel Weiskopf - IEEE Xplore Author Profile

Scheduled Maintenance on Monday 1/13/2025

Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.

IEEE.org
IEEE Xplore
IEEE SA
IEEE Spectrum
More Sites

- Donate
- Personal Sign In

Institutional Sign In

Institutional Sign In

ADVANCED SEARCH

Author details

Daniel Weiskopf

Also published under: D. Weiskopf

Publications

165

Citations

2,966

Publications by Year

20002025

Co-Authors:

Moataz AbdelaalSherif AbdulatifYasett AcuranaFrank AllgöwerMarco Amann

Show All Co-Authors (325)

Daniel Weiskopf

Also published under: D. Weiskopf

Affiliation

University of Stuttgart, Germany

Publication Topics

Supplemental Material,
Uncertain Data,
User Study,
Dimensionality Reduction Methods,
Domain Experts,
Interactive,
Normal Distribution,
Vision Research,
Visual Methods,
Visualization Techniques,
Computer Science,
Data Transformation

Biography

Daniel Weiskopf is currently a Professor, whose research interests include information visualization and scientific visualization, visual analytics, eye tracking, computer graphics, and special and general relativity. Contact him at daniel.weiskopf@visus.uni-stuttgart.de(Based on document published on 25 June 2020).

Publications

165

Citations

2,966

Publications by Year

20002025

Co-Authors:

Moataz Abdelaal
Sherif Abdulatif
Yasett Acurana
Frank Allgöwer
Marco Amann

Show All Co-Authors (325)

Author's Published Works

Search History

Showing 1-25 of 165 results

Conferences (76)

Journals (67)

Magazines (20)

Early Access Articles (2)

Sort

Filter Results

Show

Open Access Only

Range
Single Year
Daniel Weiskopf(147)
Michael Burch(34)
Fabian Beck(19)
D. Weiskopf(18)
Thomas Ertl(15)
University of Stuttgart, Germany(27)
VISUS, University of Stuttgart, Germany(21)
University of Stuttgart(20)
Visualization Research Center (VISUS), University of Stuttgart, Germany(10)
University of Stuttgart, Stuttgart, Germany(10)
IEEE Transactions on Visualization and Computer Graphics(64)
Computing in Science & Engineering(12)
IEEE Computer Graphics and Applications(8)
2016 IEEE Second Workshop on Eye Tracking and Visualization (ETVIS)(5)
2013 17th International Conference on Information Visualisation(4)
IEEE(165)
Media(16)
London, UK(8)
Baltimore, MD, USA(6)
Barcelona, Spain(4)
Lisbon, Portugal(4)
Minneapolis, MN, USA(4)
Visualization Techniques(54)
Visual Analysis(29)
Visual Clutter(26)
Visual Approach(25)
User Study(24)

Select All on Page

Sort By

Results

Uncertainty-aware Spectral Visualization

Marina Evers;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2025 | Early Access Article |

One common task in time series analysis is the visual investigation of spectra such as Fourier spectra or wavelet spectra to identify dominating frequencies. In this paper, we present the propagation of data uncertainty to the spectra and its visualization. We consider the Fourier and continuous wavelet transformations, which are two common spectral analysis methods. Deriving the propagation for t...Show More

Uncertainty-aware Spectral Visualization

Marina Evers;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2025 | Early Access Article |

Visual Analysis of Multi-Outcome Causal Graphs

Mengjie Fan;Jinlu Yu;Daniel Weiskopf;Nan Cao;Huai-Yu Wang;Liang Zhou

IEEE Transactions on Visualization and Computer Graphics

Year: 2025 | Volume: 31, Issue: 1 | Journal Article |

Cited by: Papers (1)

HTML

We introduce a visual analysis method for multiple causal graphs with different outcome variables, namely, multi-outcome causal graphs. Multi-outcome causal graphs are important in healthcare for understanding multimorbidity and comorbidity. To support the visual analysis, we collaborated with medical experts to devise two comparative visualization techniques at different stages of the analysis pr...Show More

Visual Analysis of Multi-Outcome Causal Graphs

Mengjie Fan;Jinlu Yu;Daniel Weiskopf;Nan Cao;Huai-Yu Wang;Liang Zhou

IEEE Transactions on Visualization and Computer Graphics

Year: 2025 | Volume: 31, Issue: 1 | Journal Article |

Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess

Tim Krake;Daniel Klötzl;David Hägele;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2025 | Volume: 31, Issue: 2 | Journal Article |

Cited by: Papers (2)

HTML

Seasonal-trend decomposition based on loess (STL) is a powerful tool to explore time series data visually. In this article, we present an extension of STL to uncertain data, named uncertainty-aware STL (UASTL). Our method propagates multivariate Gaussian distributions mathematically exactly through the entire analysis and visualization pipeline. Thereby, stochastic quantities shared between the co...Show More

Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess

Tim Krake;Daniel Klötzl;David Hägele;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2025 | Volume: 31, Issue: 2 | Journal Article |

Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions

Luca Reichmann;David Hägele;Daniel Weiskopf

2024 IEEE 14th Symposium on Large Data Analysis and Visualization (LDAV)

Year: 2024 | Conference Paper |

HTML

Dimensionality reduction (DR) is a well-established approach for the visualization of high-dimensional data sets. While DR methods are often applied to typical DR benchmark data sets in the literature, they might suffer from high runtime complexity and memory requirements, making them unsuitable for large data visualization especially in environments outside of high-performance computing. To perfo...Show More

Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions

Luca Reichmann;David Hägele;Daniel Weiskopf

2024 IEEE 14th Symposium on Large Data Analysis and Visualization (LDAV)

Year: 2024 | Conference Paper |

Testing the Test: Observations When Assessing Visualization Literacy of Domain Experts

Seyda Öney;Moataz Abdelaal;Kuno Kurzhals;Paul Betz;Cordula Kropp;Daniel Weiskopf

2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

Year: 2024 | Conference Paper |

HTML

Various standardized tests exist that assess individuals' visualization literacy. Their use can help to draw conclusions from studies. However, it is not taken into account that the test itself can create a pressure situation where participants might fear being exposed and assessed negatively. This is especially problematic when testing domain experts in design studies. We conducted interviews wit...Show More

Testing the Test: Observations When Assessing Visualization Literacy of Domain Experts

Seyda Öney;Moataz Abdelaal;Kuno Kurzhals;Paul Betz;Cordula Kropp;Daniel Weiskopf

2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

Year: 2024 | Conference Paper |

Bridging Quantitative and Qualitative Methods for Visualization Research: A Data/Semantics Perspective in Light of Advanced AI

Daniel Weiskopf

2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

Year: 2024 | Conference Paper |

HTML

This paper revisits the role of quantitative and qualitative methods in visualization research in the context of advancements in artificial intelligence (AI). The focus is on how we can bridge between the different methods in an integrated process of analyzing user study data. To this end, a process model of—potentially iterated—semantic enrichment and transformation of data is proposed. This join...Show More

Bridging Quantitative and Qualitative Methods for Visualization Research: A Data/Semantics Perspective in Light of Advanced AI

Daniel Weiskopf

2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

Year: 2024 | Conference Paper |

Understanding Collaborative Learning of Molecular Structures in AR With Eye Tracking

Tobias Rau;Maurice Koch;Nelusa Pathmanathan;Tobias Isenberg;Daniel Weiskopf;Michael Sedlmair;Andreas Köhn;Kuno Kurzhals

IEEE Computer Graphics and Applications

Year: 2024 | Volume: 44, Issue: 6 | Magazine Article |

HTML

We present an approach for onsite instruction of multiple students accompanied by gaze-based monitoring to observe patterns of visual attention during task solving. We focus on collaborative processes in augmented reality (AR) that play an essential role in onsite and remote teaching alike. From a teaching perspective, it is important in such scenarios to communicate content and tasks effectively,...Show More

Understanding Collaborative Learning of Molecular Structures in AR With Eye Tracking

Tobias Rau;Maurice Koch;Nelusa Pathmanathan;Tobias Isenberg;Daniel Weiskopf;Michael Sedlmair;Andreas Köhn;Kuno Kurzhals

IEEE Computer Graphics and Applications

Year: 2024 | Volume: 44, Issue: 6 | Magazine Article |

UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox

Patrick Paetzold;David Hägele;Marina Evers;Daniel Weiskopf;Oliver Deussen

2024 IEEE Workshop on Uncertainty Visualization: Applications, Techniques, Software, and Decision Frameworks

Year: 2024 | Conference Paper |

HTML

Current research provides methods to communicate uncertainty and adapts classical algorithms of the visualization pipeline to take the uncertainty into account. Various existing visualization frameworks include methods to present uncertain data but do not offer transformation techniques tailored to uncertain data. Therefore, we propose a software package for uncertainty-aware data analysis in Pyth...Show More

UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox

Patrick Paetzold;David Hägele;Marina Evers;Daniel Weiskopf;Oliver Deussen

2024 IEEE Workshop on Uncertainty Visualization: Applications, Techniques, Software, and Decision Frameworks

Year: 2024 | Conference Paper |

Maximum Entropy and Quantized Metric Models for Absolute Category Ratings

Dietmar Saupe;Krzysztof Rusek;David Hägele;Daniel Weiskopf;Lucjan Janowski

IEEE Signal Processing Letters

Year: 2024 | Volume: 31 | Journal Article |

HTML

The datasets of most image quality assessment studies contain ratings on a categorical scale with five levels, from bad (1) to excellent (5). For each stimulus, the number of ratings from 1 to 5 is summarized and given in the form of the mean opinion score. In this study, we investigate families of multinomial probability distributions parameterized by mean and variance that are used to fit the em...Show More

Maximum Entropy and Quantized Metric Models for Absolute Category Ratings

Dietmar Saupe;Krzysztof Rusek;David Hägele;Daniel Weiskopf;Lucjan Janowski

IEEE Signal Processing Letters

Year: 2024 | Volume: 31 | Journal Article |

Active Gaze Labeling: Visualization for Trust Building

Maurice Koch;Nan Cao;Daniel Weiskopf;Kuno Kurzhals

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Early Access Article |

Cited by: Papers (1)

Areas of interest (AOIs) are well-established means of providing semantic information for visualizing, analyzing, and classifying gaze data. However, the usual manual annotation of AOIs is time-consuming and further impaired by ambiguities in label assignments. To address these issues, we present an interactive labeling approach that combines visualization, machine learning, and user-centered expl...Show More

Active Gaze Labeling: Visualization for Trust Building

Maurice Koch;Nan Cao;Daniel Weiskopf;Kuno Kurzhals

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Early Access Article |

Comparative Evaluation of Animated Scatter Plot Transitions

Nils Rodrigues;Frederik L. Dennig;Vincent Brandt;Daniel A. Keim;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 6 | Journal Article |

Cited by: Papers (1)

HTML

Scatter plots are popular for displaying 2D data, but in practice, many data sets have more than two dimensions. For the analysis of such multivariate data, it is often necessary to switch between scatter plots of different dimension pairs, e.g., in a scatter plot matrix (SPLOM). Alternative approaches include a “grand tour” for an overview of the entire data set or creating artificial axes from d...Show More

Comparative Evaluation of Animated Scatter Plot Transitions

Nils Rodrigues;Frederik L. Dennig;Vincent Brandt;Daniel A. Keim;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 6 | Journal Article |

Scalability in Visualization

Gaëlle Richer;Alexis Pister;Moataz Abdelaal;Jean-Daniel Fekete;Michael Sedlmair;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 7 | Journal Article |

Cited by: Papers (16)

HTML

We introduce a conceptual model for scalability designed for visualization research. With this model, we systematically analyze over 120 visualization publications from 1990 to 2020 to characterize the different notions of scalability in these works. While many article have addressed scalability issues, our survey identifies a lack of consistency in the use of the term in the visualization researc...Show More

Scalability in Visualization

Gaëlle Richer;Alexis Pister;Moataz Abdelaal;Jean-Daniel Fekete;Michael Sedlmair;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 7 | Journal Article |

Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations

Moataz Abdelaal;Nathan D. Schiele;Katrin Angerbauer;Kuno Kurzhals;Michael Sedlmair;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 1 | Journal Article |

Cited by: Papers (9)

HTML

This work investigates and compares the performance of node-link diagrams, adjacency matrices, and bipartite layouts for visualizing networks. In a crowd-sourced user study ($\mathrm{n}=150$), we measure the task accuracy and completion time of the three representations for different network classes and properties. In contrast to the literature, which covers mostly topology-based tasks (e.g., path...Show More

Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations

Moataz Abdelaal;Nathan D. Schiele;Katrin Angerbauer;Kuno Kurzhals;Michael Sedlmair;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 1 | Journal Article |

Uncertainty-Aware Multidimensional Scaling

David Hägele;Tim Krake;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 1 | Journal Article |

Cited by: Papers (4)

HTML

We present an extension of multidimensional scaling (MDS) to uncertain data, facilitating uncertainty visualization of multidimensional data. Our approach uses local projection operators that map high-dimensional random vectors to low-dimensional space to formulate a generalized stress. In this way, our generic model supports arbitrary distributions and various stress types. We use our uncertainty...Show More

Uncertainty-Aware Multidimensional Scaling

David Hägele;Tim Krake;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 1 | Journal Article |

Constrained Dynamic Mode Decomposition

Tim Krake;Daniel Klötzl;Bernhard Eberhardt;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 1 | Journal Article |

Cited by: Papers (4)

HTML

Frequency-based decomposition of time series data is used in many visualization applications. Most of these decomposition methods (such as Fourier transform or singular spectrum analysis) only provide interaction via pre- and post-processing, but no means to influence the core algorithm. A method that also belongs to this class is Dynamic Mode Decomposition (DMD), a spectral decomposition method t...Show More

Constrained Dynamic Mode Decomposition

Tim Krake;Daniel Klötzl;Bernhard Eberhardt;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 1 | Journal Article |

Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution

Nils Rodrigues;Christoph Schulz;Sören Döring;Daniel Baumgartner;Tim Krake;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 1 | Journal Article |

Cited by: Papers (1)

HTML

We introduce relaxed dot plots as an improvement of nonlinear dot plots for unit visualization. Our plots produce more faithful data representations and reduce moiré effects. Their contour is based on a customized kernel frequency estimation to match the shape of the distribution of underlying data values. Previous nonlinear layouts introduce column-centric nonlinear scaling of dot diameters for v...Show More

Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution

Nils Rodrigues;Christoph Schulz;Sören Döring;Daniel Baumgartner;Tim Krake;Daniel Weiskopf

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 1 | Journal Article |

Interactive Analysis of Post-Silicon Validation Data

Andres Lalama;Johannes Knittel;Steffen Koch;Daniel Weiskopf;Thomas Ertl;Sarah Rottacker;Raphaël Latty;Jochen Rivoir

2022 First International Workshop on Visualization in Testing of Hardware, Software, and Manufacturing (TestVis)

Year: 2022 | Conference Paper |

HTML

Analyzing post-silicon validation datasets to spot bugs and obtain hints for design improvements challenges validation engineers with complex and sometimes subtle problems. Through experience, engineers gain accuracy and speed in recognizing the cause of a problem, but analyzing the data remains a tedious and time-consuming process involving substantial manual effort. Sometimes, validation enginee...Show More

Interactive Analysis of Post-Silicon Validation Data

Andres Lalama;Johannes Knittel;Steffen Koch;Daniel Weiskopf;Thomas Ertl;Sarah Rottacker;Raphaël Latty;Jochen Rivoir

2022 First International Workshop on Visualization in Testing of Hardware, Software, and Manufacturing (TestVis)

Year: 2022 | Conference Paper |

Power Overwhelming: Quantifying the Energy Cost of Visualisation

Christoph Müller;Moritz Heinemann;Daniel Weiskopf;Thomas Ertl

2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

HTML

GPUs are the power-hungry tool of many visualisation researchers. However, their energy consumption has mostly been investigated outside the visualisation community, albeit our algorithms can generate more complex workloads than compute kernels. Additionally, a raising number of web-based visualisations potentially makes consumers other than the GPU more relevant. We present measurement setups for...Show More

Power Overwhelming: Quantifying the Energy Cost of Visualisation

Christoph Müller;Moritz Heinemann;Daniel Weiskopf;Thomas Ertl

2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

Year: 2022 | Conference Paper |

Research Data Curation in Visualization : Position Paper

Dimitar Garkov;Christoph Müller;Matthias Braun;Daniel Weiskopf;Falk Schreiber

2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

HTML

Research data curation is the act of carefully preparing research data and artifacts for sharing and long-term preservation. Research data management is centrally implemented and formally defined in a data management plan to enable data curation. In tandem, data curation and management facilitate research repeatability. In contrast to other research fields, data curation and management in visualiz...Show More

Research Data Curation in Visualization : Position Paper

Dimitar Garkov;Christoph Müller;Matthias Braun;Daniel Weiskopf;Falk Schreiber

2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

Year: 2022 | Conference Paper |

Reduced Connectivity for Local Bilinear Jacobi Sets

Daniel Klötzl;Tim Krake;Youjia Zhou;Jonathan Stober;Kathrin Schulte;Ingrid Hotz;Bei Wang;Daniel Weiskopf

2022 Topological Data Analysis and Visualization (TopoInVis)

Year: 2022 | Conference Paper |

HTML

We present a new topological connection method for the local bilinear computation of Jacobi sets that improves the visual representation while preserving the topological structure and geometric configuration. To this end, the topological structure of the local bilinear method is utilized, which is given by the nerve complex of the traditional piecewise linear method. Since the nerve complex consis...Show More

Reduced Connectivity for Local Bilinear Jacobi Sets

Daniel Klötzl;Tim Krake;Youjia Zhou;Jonathan Stober;Kathrin Schulte;Ingrid Hotz;Bei Wang;Daniel Weiskopf

2022 Topological Data Analysis and Visualization (TopoInVis)

Year: 2022 | Conference Paper |

Intelligent Methods for Test and Reliability

H. Amrouch;J. Anders;S. Becker;M. Betka;G. Bleher;P. Domanski;N. Elhamawy;T. Ertl;A. Gatzastras;P. Genssler;S. Hasler;M. Heinrich;A. van Hoorn;H. Jafarzadeh;I. Kallfass;F. Klemme;S. Koch;R. Küsters;A. Lalama;R. Latty;Y. Liao;N. Lylina;Z. Najafi Haghi;D. Pflüger;I. Polian;J. Rivoir;M. Sauer;D. Schwachhofer;S. Templin;C. Volmer;S. Wagner;D. Weiskopf;H.-J. Wunderlich;B. Yang;M. Zimmermann

2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

HTML

Test methods that can keep up with the ongoing increase in complexity of semiconductor products and their underlying technologies are an essential prerequisite for maintaining quality and safety of our daily lives and for continued success of our economies and societies. There is a huge potential how test methods can benefit from recent breakthroughs in domains such as artificial intelligence, dat...Show More

Intelligent Methods for Test and Reliability

H. Amrouch;J. Anders;S. Becker;M. Betka;G. Bleher;P. Domanski;N. Elhamawy;T. Ertl;A. Gatzastras;P. Genssler;S. Hasler;M. Heinrich;A. van Hoorn;H. Jafarzadeh;I. Kallfass;F. Klemme;S. Koch;R. Küsters;A. Lalama;R. Latty;Y. Liao;N. Lylina;Z. Najafi Haghi;D. Pflüger;I. Polian;J. Rivoir;M. Sauer;D. Schwachhofer;S. Templin;C. Volmer;S. Wagner;D. Weiskopf;H.-J. Wunderlich;B. Yang;M. Zimmermann

2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)

Year: 2022 | Conference Paper |

Situated Visual Analysis and Live Monitoring for Manufacturing

Michael Becher;Dominik Herr;Christoph Müller;Kuno Kurzhals;Guido Reina;Lena Wagner;Thomas Ertl;Daniel Weiskopf

IEEE Computer Graphics and Applications

Year: 2022 | Volume: 42, Issue: 2 | Magazine Article |

Cited by: Papers (9)

HTML

Modern machines continuously log status reports over long periods of time, which are valuable data to optimize working routines. Data visualization is a commonly used tool to gain insights into these data, mostly in retrospective (e.g., to determine causal dependencies between the faults of different machines). We present an approach to bring such visual analyses to the shop floor to support react...Show More

Situated Visual Analysis and Live Monitoring for Manufacturing

Michael Becher;Dominik Herr;Christoph Müller;Kuno Kurzhals;Guido Reina;Lena Wagner;Thomas Ertl;Daniel Weiskopf

IEEE Computer Graphics and Applications

Year: 2022 | Volume: 42, Issue: 2 | Magazine Article |

Visualization for Architecture, Engineering, and Construction: Shaping the Future of Our Built World

Moataz Abdelaal;Felix Amtsberg;Michael Becher;Rebeca Duque Estrada;Fabian Kannenberg;Aimée Sousa Calepso;Hans Jakob Wagner;Guido Reina;Michael Sedlmair;Achim Menges;Daniel Weiskopf

IEEE Computer Graphics and Applications

Year: 2022 | Volume: 42, Issue: 2 | Magazine Article |

Cited by: Papers (11)

HTML

Our built world is one of the most important factors for a livable future, accounting for massive impact on resource and energy use, as well as climate change, but also the social and economic aspects that come with population growth. The architecture, engineering, and construction industry is facing the challenge that it needs to substantially increase its productivity, let alone the quality of b...Show More

Visualization for Architecture, Engineering, and Construction: Shaping the Future of Our Built World

Moataz Abdelaal;Felix Amtsberg;Michael Becher;Rebeca Duque Estrada;Fabian Kannenberg;Aimée Sousa Calepso;Hans Jakob Wagner;Guido Reina;Michael Sedlmair;Achim Menges;Daniel Weiskopf

IEEE Computer Graphics and Applications

Year: 2022 | Volume: 42, Issue: 2 | Magazine Article |

Age-Net: An MRI-Based Iterative Framework for Brain Biological Age Estimation

Karim Armanious;Sherif Abdulatif;Wenbin Shi;Shashank Salian;Thomas Küstner;Daniel Weiskopf;Tobias Hepp;Sergios Gatidis;Bin Yang

IEEE Transactions on Medical Imaging

Year: 2021 | Volume: 40, Issue: 7 | Journal Article |

Cited by: Papers (26)

HTML

The concept of biological age (BA) - although important in clinical practice - is hard to grasp mainly due to the lack of a clearly defined reference standard. For specific applications, especially in pediatrics, medical image data are used for BA estimation in a routine clinical context. Beyond this young age group, BA estimation is mostly restricted to whole-body assessment using non-imaging ind...Show More

Age-Net: An MRI-Based Iterative Framework for Brain Biological Age Estimation

Karim Armanious;Sherif Abdulatif;Wenbin Shi;Shashank Salian;Thomas Küstner;Daniel Weiskopf;Tobias Hepp;Sergios Gatidis;Bin Yang

IEEE Transactions on Medical Imaging

Year: 2021 | Volume: 40, Issue: 7 | Journal Article |

The State of the Art in Empirical User Evaluation of Graph Visualizations

Michael Burch;Weidong Huang;Mathew Wakefield;Helen C. Purchase;Daniel Weiskopf;Jie Hua

Year: 2021 | Volume: 9 | Journal Article |

Cited by: Papers (19)

HTML

While graph drawing focuses more on the aesthetic representation of node-link diagrams, graph visualization takes into account other visual metaphors making them useful for graph exploration tasks in information visualization and visual analytics. Although there are aesthetic graph drawing criteria that describe how a graph should be presented to make it faster and more reliably explorable, many c...Show More

The State of the Art in Empirical User Evaluation of Graph Visualizations

Michael Burch;Weidong Huang;Mathew Wakefield;Helen C. Purchase;Daniel Weiskopf;Jie Hua

Year: 2021 | Volume: 9 | Journal Article |

IEEE Personal Account

Change username/password

Purchase Details

Payment Options
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

Follow

About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting | Sitemap | IEEE Privacy Policy

A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

© Copyright 2025 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies.

IEEE Account

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

About IEEE Xplore
Contact Us
Help
Accessibility
Terms of Use
Nondiscrimination Policy
Sitemap
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

Test Whats new message.