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Investigation of Activation Functions for Generalized Learning Vector Quantization.

, , , , and . WSOM+, volume 976 of Advances in Intelligent Systems and Computing, page 179-188. Springer, (2019)

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Trustworthiness and Confidence of Gait Phase Predictions in Changing Environments Using Interpretable Classifier Models., , , and . ICONIP (2), volume 13624 of Lecture Notes in Computer Science, page 379-390. Springer, (2022)Investigation of Activation Functions for Generalized Learning Vector Quantization., , , , and . WSOM+, volume 976 of Advances in Intelligent Systems and Computing, page 179-188. Springer, (2019)Detecting Oncoming Vehicles at Night in Urban Scenarios - An Annotation Proof-Of-Concept., , , , , , , , , and . IV, page 2117-2124. IEEE, (2024)Quantum-Inspired Learning Vector Quantization for Classification Learning., , , , and . ESANN, page 279-284. (2020)DropConnect for Evaluation of Classification Stability in Learning Vector Quantization., , and . ESANN, (2019)A Learning Vector Quantization Architecture for Transfer Learning Based Classification in Case of Multiple Sources by Means of Null-Space Evaluation., , , , , and . IDA, volume 13205 of Lecture Notes in Computer Science, page 354-364. Springer, (2022)Quantum-inspired learning vector quantizers for prototype-based classification., , , , and . Neural Comput. Appl., 34 (1): 79-88 (2022)RecLVQ: Recurrent Learning Vector Quantization., , and . ESANN, (2021)