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Machine Learning and Data Analytics Lab
Friedrich-Alexander-Universität Erlangen-Nürnberg
Technische Fakultät
Department Artificial Intelligence in Biomedical Engineering (AIBE)
Overview
Publications
(681)
Research Data
(1)
Research Fields
(6)
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Journal article
Journal article
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Book chapter / Article in edited volumes
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Machine Learning from Biomechanical SimulaIons for an "in the Wild" Movement Analysis (2021)
Dorschky E, Nitschke M, van den Bogert AJ, Koelewijn A, Eskofier B
Conference contribution, Abstract of lecture
Identification of individuals through a new Gait Recognition Method (2021)
Dib W, Ghanem K, Nedil M, Ababou A, Eskofier B
Conference contribution
HeMoG: A White-Box Model to Unveil the Connection Between Saliency Information and Human Head Motion in Virtual Reality (2021)
Rondon MFR, Zanca D, Melacci S, Gori M, Sassatelli L
Conference contribution
Hess Screen Revised: How Eye Tracking and Virtual Reality change Strabismus Assessment (2021)
Mehringer W, Wirth M, Risch F, Roth D, Michelson G, Michelson G, Eskofier B
Conference contribution, Conference Contribution
ICDAR 2021 Competition on On-Line Signature Verification (2021)
Tolosana R, Vera-Rodriguez R, Gonzalez-Garcia C, Fierrez J, Rengifo S, Morales A, Ortega-Garcia J, et al.
Conference contribution
System Design for a Data-Driven and Explainable Customer Sentiment Monitor Using IoT and Enterprise Data (2021)
Nguyen A, Foerstel S, Kittler T, Kurzyukov A, Schwinn L, Zanca D, Hipp T, et al.
Journal article, Original article
Consensus based framework for digital mobility monitoring (2021)
Kluge F, Del Din S, Cereatti A, Gaßner H, Hansen C, Helbostad JL, Klucken J, et al.
Journal article
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks (2021)
Schwinn L, Raab R, Nguyen A, Zanca D, Eskofier B
Conference contribution, Conference Contribution
Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks (2021)
Schwinn L, Nguyen A, Raab R, Zanca D, Eskofier B, Tenbrinck D, Burger M
Conference contribution, Conference Contribution
Identifying untrustworthy predictions in neural networks by geometric gradient analysis (2021)
Schwinn L, Nguyen A, Raab R, Bungert L, Tenbrinck D, Zanca D, Burger M, Eskofier B
Conference contribution, Conference Contribution
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