Refine
H-BRS Bibliography
- yes (221) (remove)
Departments, institutes and facilities
- Fachbereich Wirtschaftswissenschaften (58)
- Fachbereich Informatik (43)
- Fachbereich Sozialpolitik und Soziale Sicherung (37)
- Fachbereich Ingenieurwissenschaften und Kommunikation (32)
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (28)
- Fachbereich Angewandte Naturwissenschaften (26)
- Institut für Verbraucherinformatik (IVI) (11)
- Institut für Cyber Security & Privacy (ICSP) (9)
- Institute of Visual Computing (IVC) (8)
- Internationales Zentrum für Nachhaltige Entwicklung (IZNE) (7)
- Graduierteninstitut (6)
- Institut für Medienentwicklung und -analyse (IMEA) (6)
- Zentrum für Innovation und Entwicklung in der Lehre (ZIEL) (6)
- Institut für funktionale Gen-Analytik (IFGA) (5)
- Bibliothek (4)
- Zentrum für Ethik und Verantwortung (ZEV) (4)
- Centrum für Entrepreneurship, Innovation und Mittelstand (CENTIM) (3)
- Institut für Sicherheitsforschung (ISF) (2)
- Institut für Detektionstechnologien (IDT) (1)
- Präsidium (1)
- Sprachenzentrum (1)
Document Type
- Conference Object (53)
- Article (50)
- Part of a Book (50)
- Book (monograph, edited volume) (18)
- Preprint (12)
- Contribution to a Periodical (8)
- Research Data (6)
- Doctoral Thesis (6)
- Master's Thesis (5)
- Report (4)
- Conference Proceedings (2)
- Other (2)
- Book review (2)
- Working Paper (2)
- Part of Periodical (1)
Year of publication
- 2022 (221) (remove)
Has Fulltext
- no (221) (remove)
Keywords
- Lehrbuch (4)
- Medienästhetik (4)
- Medien (3)
- Medienwissenschaft (3)
- usable privacy (3)
- Cathepsin K (2)
- Chemometrics (2)
- Control Systems and Automation (2)
- Design (2)
- Electrical Machines and Power Electronics (2)
论“数字化大学”的内涵及发展
(2022)
Zum Geleit
(2022)
Wie KI Innere Führung lernt
(2022)
Dass sich künstliche Intelligenz (KI) weltweit ausgebreitet hat, ist eine Binsenwahrheit. Die rasche und unaufhaltsame Proliferation von KI der letzten zehn Jahre spricht für sich, und längst ziehen auch Gesetzgeber und Regulierungsbehörden nach, um KI und ihre Technikfolgen einzuhegen. Für Deutschland relevante Gestaltungsanforderungen haben die High-Level Expert Group on Artificial Intelligence der Europäischen Kommission (HLEG AI) und auf nationaler Ebene die Datenethikkommission der Bundesregierung (DEK) und die Enquetekommission Künstliche Intelligenz des Deutschen Bundestags (EKKI) geäußert.
Wehren erlaubt
(2022)
Virtual exchange
(2022)
Vection underwater
(2022)
TSEM: Temporally Weighted Spatiotemporal Explainable Neural Network for Multivariate Time Series
(2022)
Deep learning has become a one-size-fits-all solution for technical and business domains thanks to its flexibility and adaptability. It is implemented using opaque models, which unfortunately undermines the outcome trustworthiness. In order to have a better understanding of the behavior of a system, particularly one driven by time series, a look inside a deep learning model so-called posthoc eXplainable Artificial Intelligence (XAI) approaches, is important. There are two major types of XAI for time series data, namely model-agnostic and model-specific. Model-specific approach is considered in this work. While other approaches employ either Class Activation Mapping (CAM) or Attention Mechanism, we merge the two strategies into a single system, simply called the Temporally Weighted Spatiotemporal Explainable Neural Network for Multivariate Time Series (TSEM). TSEM combines the capabilities of RNN and CNN models in such a way that RNN hidden units are employed as attention weights for the CNN feature maps temporal axis. The result shows that TSEM outperforms XCM. It is similar to STAM in terms of accuracy, while also satisfying a number of interpretability criteria, including causality, fidelity, and spatiotemporality.
Regions and their innovation ecosystems have increasingly become of interest to CSCW research as the context in which work, research and design takes place. Our study adds to this growing discourse, by providing preliminary data and reflections from an ongoing attempt to intervene and support a regional innovation ecosystem. We report on the benefits and shortcomings of a practice-oriented approach in such regional projects and highlight the importance of relations and the notion of spillover. Lastly, we discuss methodological and pragmatic hurdles that CSCW research needs to overcome in order to support regional innovation ecosystems successfully.