Seuraa
David Sessler
David Sessler
Student MSc. Visual Computing, TU Darmstadt
Vahvistettu sähköpostiosoite verkkotunnuksessa gris.informatik.tu-darmstadt.de
Nimike
Viittaukset
Viittaukset
Vuosi
Using dashboard networks to visualize multiple patient histories: a design study on post-operative prostate cancer
J Bernard, D Sessler, J Kohlhammer, RA Ruddle
IEEE transactions on visualization and computer graphics 25 (3), 1615-1628, 2018
632018
A visual-interactive system for prostate cancer cohort analysis
J Bernard, D Sessler, T May, T Schlomm, D Pehrke, J Kohlhammer
IEEE computer graphics and applications 35 (3), 44-55, 2015
612015
A visual active learning system for the assessment of patient well-being in prostate cancer research
J Bernard, D Sessler, A Bannach, T May, J Kohlhammer
Proceedings of the 2015 Workshop on Visual Analytics in Healthcare, 1-8, 2015
372015
Netcapvis: Web-based progressive visual analytics for network packet captures
A Ulmer, D Sessler, J Kohlhammer
2019 IEEE Symposium on Visualization for Cyber Security (VizSec), 1-10, 2019
272019
Visual-interactive identification of anomalous ip-block behavior using geo-ip data
A Ulmer, M Schufrin, D Sessler, J Kohlhammer
2018 IEEE Symposium on Visualization for Cyber Security (VizSec), 1-8, 2018
172018
Visual-interactive similarity search for complex objects by example of soccer player analysis
J Bernard, C Ritter, D Sessler, M Zeppelzauer, J Kohlhammer, D Fellner
arXiv preprint arXiv:1703.03385, 2017
162017
Uncovering chains of infections through spatio-temporal and visual analysis of COVID-19 contact traces
D Antweiler, D Sessler, M Rossknecht, B Abb, S Ginzel, J Kohlhammer
Computers & Graphics 106, 1-8, 2022
132022
Towards the Detection and Visual Analysis of COVID-19 Infection Clusters.
D Antweiler, D Sessler, S Ginzel, J Kohlhammer
EuroVA@ EuroVis, 43-47, 2021
132021
A visual-interactive system for prostate cancer stratifications
J Bernard, D Sessler, T May, T Schlomm, D Pehrke, J Kohlhammer
Proc. IEEE VIS Workshop Visualizing Electronic Health Record Data 10, 2014
132014
User-based visual-interactive similarity definition for mixed data objects: concept and first implementation
J Bernard, D Sessler, T Ruppert
Václav Skala-UNION Agency, 2014
112014
Towards a comprehensive cohort visualization of patients with inflammatory bowel disease
S Ahmad, D Sessler, J Kohlhammer
2021 IEEE Workshop on Visual Analytics in Healthcare (VAHC), 25-29, 2021
62021
ProBGP: Progressive visual analytics of live BGP updates
A Ulmer, D Sessler, J Kohlhammer
Computer Graphics Forum 40 (3), 37-48, 2021
32021
Information visualization interface on home router traffic data for laypersons
M Schufrin, D Sessler, SL Reynolds, S Ahmad, T Mertz, J Kohlhammer
Proceedings of the International Conference on Advanced Visual Interfaces, 1-3, 2020
32020
Visual-Interactive Exploration of Relations Between Time-Oriented Data and Multivariate Data.
J Bernard, D Sessler, M Steiger, M Spott, J Kohlhammer
EuroVA@ EuroVis, 49-53, 2016
32016
Towards a user-defined visual-interactive definition of similarity functions for mixed data
J Bernard, M Hutter, D Sessler, T Schreck, M Behrisch, J Kohlhamme
2014 IEEE Conference on Visual Analytics Science and Technology (VAST), 227-228, 2014
32014
Towards bridging the gap between visual cybersecurity analytics and non-experts by means of user experience design
M Schufrin, A Ulmer, D Sessler, J Kohlhammer
2019 IEEE Symposium on Visualization for Cyber Security (VizSec), 2018
22018
Adopting mental similarity notions of categorical data objects to algorithmic similarity functions
D Sessler, J Bernard, A Kuijper, J Kohlhammer
Vision, Modelling and Visualization (VMV), Poster, 2014
12014
Cohort Visualization and Analysis of Patients with Inflammatory Bowel Disease
D Sessler, S Ahmad, J Kohlhammer
2023 Workshop on Visual Analytics in Healthcare (VAHC), 41-43, 2023
2023
Towards the Visualization of Aggregated Class Activation Maps to Analyse the Global Contribution of Class Features
I Cherepanov, D Sessler, A Ulmer, H Lücke-Tieke, J Kohlhammer
World Conference on Explainable Artificial Intelligence, 3-23, 2023
2023
Towards Combining Attribute-based and Time Series-based Visual Querying.
D Sessler, M Spott, DD Nauck, W Harmer, J Kohlhammer, J Bernard
EuroVis (Posters), 73-75, 2016
2016
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Artikkelit 1–20