PUBLIKATIONSSERVER

Wolfram Schenck

https://orcid.org/0000-0003-3300-2048

50 Publikationen

Alle markieren

[50]
2024 | Konferenzbeitrag | FH-PUB-ID: 4699
Technical Readiness of Prescriptive Analytics Platforms: A Survey
M. Niederhaus, N. Migenda, J. Weller, W. Schenck, M. Kohlhase, in: IEEE (Ed.), 2024 35th Conference of Open Innovations Association (FRUCT), IEEE, 2024, pp. 509–519.
HSBI-PUB | DOI
 
[49]
2024 | Artikel | FH-PUB-ID: 4698
NGPCA: Clustering of high-dimensional and non-stationary data streams
N. Migenda, R. Möller, W. Schenck, Software Impacts 20 (2024).
HSBI-PUB | DOI
 
[48]
2024 | Buchbeitrag | FH-PUB-ID: 4915
Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, R. Liu, A. Wegel, S. von Enzberg, M. Kohlhase, W. Schenck, R. Dumitrescu, in: O. Niggemann, J. Beyerer, M. Krantz, C. Kühnert (Eds.), Machine Learning for Cyber-Physical Systems. Selected Papers from the International Conference ML4CPS 2023, Springer Nature Switzerland, Cham, 2024, pp. 89–100.
HSBI-PUB | DOI
 
[47]
2024 | Artikel | FH-PUB-ID: 4913
Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, Y. Naik, T. Heuwinkel, A. Kühn, M. Kohlhase, W. Schenck, R. Dumitrescu, Mathematics 12 (2024).
HSBI-PUB | DOI
 
[46]
2024 | Konferenzbeitrag | FH-PUB-ID: 4644
Exploratory Analysis of Machine Learning Methods for the Prognosis of Falls in Elderly Care Based on Accelerometer Data
L. Klein, C. Ostrau, M. Thies, W. Schenck, U. Rückert, in: D. Salvi, P. Van Gorp, S.A. Shah (Eds.), Pervasive Computing Technologies for Healthcare. 17th EAI International Conference, PervasiveHealth 2023, Malmö, Sweden, November 27-29, 2023, Proceedings, Springer Nature Switzerland, Cham, 2024, pp. 423–437.
HSBI-PUB | DOI
 
[45]
2024 | Artikel | FH-PUB-ID: 4050
Adaptive local Principal Component Analysis improves the clustering of high-dimensional data
N. Migenda, R. Möller, W. Schenck, Pattern Recognition 146 (2024).
HSBI-PUB | DOI
 
[44]
2023 | Konferenzbeitrag | FH-PUB-ID: 4700
Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories
J. Weller, N. Migenda, A. Wegel, M. Kohlhase, W. Schenck, R. Dumitrescu, in: IEEE (Ed.), 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS), IEEE, 2023, pp. 1–7.
HSBI-PUB | DOI
 
[43]
2023 | Konferenzbeitrag | FH-PUB-ID: 4293
Object View Prediction with Aleatoric Uncertainty for Robotic Grasping
C. Schwan, W. Schenck, in: 2023 International Joint Conference on Neural Networks (IJCNN), IEEE, 2023, pp. 1–8.
HSBI-PUB | DOI
 
[42]
2023 | Artikel | FH-PUB-ID: 2774 | OA
A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions
A. Tharwat, W. Schenck, Mathematics 11 (2023).
HSBI-PUB | DOI | Download (ext.)
 
[41]
2023 | Artikel | FH-PUB-ID: 3453 | OA
sEMG-based prediction of human forearm movements utilizing a biomechanical model based on individual anatomical/ physiological measures and a reduced set of optimization parameters
N. Grimmelsmann, M. Mechtenberg, W. Schenck, H.G. Meyer, A. Schneider, PLOS ONE 18 (2023).
HSBI-PUB | DOI | Download (ext.)
 
[40]
2022 | Artikel | FH-PUB-ID: 1799 | OA
Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks
K. Vandevoorde, L. Vollenkemper, C. Schwan, M. Kohlhase, W. Schenck, Sensors 22 (2022).
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[39]
2022 | Konferenzbeitrag | FH-PUB-ID: 2945
Impact of different loss functions on denoising of microscopic images
Z.H. Shah, M. Muller, B. Hammer, T. Huser, W. Schenck, in: 2022 International Joint Conference on Neural Networks (IJCNN), IEEE, 2022, pp. 1–10.
HSBI-PUB | DOI
 
[38]
2022 | Artikel | FH-PUB-ID: 2944 | OA
Open set task augmentation facilitates generalization of deep neural networks trained on small data sets
W. Zai El Amri, F. Reinhart, W. Schenck, Neural Computing and Applications 34 (2022) 6067–6083.
HSBI-PUB | DOI | Download (ext.)
 
[37]
2022 | Konferenzbeitrag | FH-PUB-ID: 2776 | OA
Design of Interpretable Machine Learning Tasks for the Application to Industrial Order Picking
C. Schwan, W. Schenck, in: J. Jasperneite, V. Lohweg (Eds.), Kommunikation und Bildverarbeitung in der Automation. Ausgewählte Beiträge der Jahreskolloquien KommA und BVAu 2020, Springer Berlin Heidelberg, Berlin, Heidelberg, 2022, pp. 291–303.
HSBI-PUB | DOI | Download (ext.)
 
[36]
2022 | Artikel | FH-PUB-ID: 2775 | OA
A Novel Low-Query-Budget Active Learner with Pseudo-Labels for Imbalanced Data
A. Tharwat, W. Schenck, Mathematics 10 (2022).
HSBI-PUB | DOI | Download (ext.)
 
[35]
2022 | Konferenzbeitrag | FH-PUB-ID: 2569
Collaborative System for Question Answering in German Case Law Documents
C. Hoppe, N. Migenda, D. Pelkmann, D.A. Hötte, W. Schenck, in: L.M. Camarinha-Matos, A. Ortiz, X. Boucher, A.L. Osório (Eds.), Collaborative Networks in Digitalization and Society 5.0, Springer International Publishing, Cham, 2022, pp. 303–312.
HSBI-PUB | DOI
 
[34]
2021 | Artikel | FH-PUB-ID: 1202
A conceptual and practical comparison of PSO-style optimization algorithms
A. Tharwat, W. Schenck, Expert Systems with Applications 167 (2021).
HSBI-PUB | DOI
 
[33]
2021 | Artikel | FH-PUB-ID: 1201 | OA
Deep-learning based denoising and reconstruction of super-resolution structured illumination microscopy images
Z.H. Shah, M. Müller, T.-C. Wang, P.M. Scheidig, A. Schneider, M. Schüttpelz, T. Huser, W. Schenck, Photonics Research 9 (2021).
HSBI-PUB | DOI | Download (ext.)
 
[32]
2021 | Konferenzbeitrag | FH-PUB-ID: 2570
Towards Intelligent Legal Advisors for Document Retrieval and Question-Answering in German Legal Documents
C. Hoppe, D. Pelkmann, N. Migenda, D.A. Hotte, W. Schenck, in: 2021 IEEE Fourth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), IEEE, 2021, pp. 29–32.
HSBI-PUB | DOI
 
[31]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Advanced Data Analytics Platform for Manufacturing Companies
T. Voigt, N. Migenda, M. Schöne, D. Pelkmann, M. Fricke, W. Schenck, M. Kohlhase, in: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, pp. 01–08.
HSBI-PUB | DOI
 
[30]
2021 | Konferenzbeitrag | FH-PUB-ID: 2572
Variational Autoencoder based Novelty Detection for Real-World Time Series
L. Steinmann, N. Migenda, T. Voigt, M. Kohlhase, W. Schenck, in: 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, New York, NY, USA, 2021, pp. 1–7.
HSBI-PUB | DOI
 
[29]
2021 | Artikel | FH-PUB-ID: 1203
Adaptive dimensionality reduction for neural network-based online principal component analysis
N. Migenda, R. Möller, W. Schenck, PLOS ONE 16 (2021).
HSBI-PUB | DOI
 
[28]
2021 | Artikel | FH-PUB-ID: 2777
Population initialization techniques for evolutionary algorithms for single-objective constrained optimization problems: Deterministic vs. stochastic techniques
A. Tharwat, W. Schenck, Swarm and Evolutionary Computation 67 (2021).
HSBI-PUB | DOI
 
[27]
2020 | Artikel | FH-PUB-ID: 1204
Balancing Exploration and Exploitation: A novel active learner for imbalanced data
A. Tharwat, W. Schenck, Knowledge-Based Systems 210 (2020).
HSBI-PUB | DOI
 
[26]
2020 | Konferenzbeitrag | FH-PUB-ID: 1206
How to Label? Combining Experts’ Knowledge for German Text Classification
D. Pelkmann, A. Tharwat, W. Schenck, in: 2020 7th Swiss Conference on Data Science (SDS), IEEE, 2020, pp. 61–62.
HSBI-PUB | DOI
 
[25]
2020 | Konferenzbeitrag | FH-PUB-ID: 1207
Visual Movement Prediction for Stable Grasp Point Detection
C. Schwan, W. Schenck, in: L. Iliadis, P.P. Angelov, C. Jayne, E. Pimenidis (Eds.), Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. Proceedings of the EANN 2020, Springer International Publishing, Cham, 2020, pp. 70–81.
HSBI-PUB | DOI
 
[24]
2020 | Diskussionspapier | FH-PUB-ID: 2778 | OA
Deep-learning based denoising and reconstruction of super-resolution structured illumination microscopy images
Z.H. Shah, M. Müller, T.-C. Wang, P.M. Scheidig, A. Schneider, M. Schüttpelz, T. Huser, W. Schenck, Deep-Learning Based Denoising and Reconstruction of Super-Resolution Structured Illumination Microscopy Images, Cold Spring Harbor Laboratory, 2020.
HSBI-PUB | DOI | Download (ext.)
 
[23]
2020 | Konferenzbeitrag | FH-PUB-ID: 2574
Adaptive Dimensionality Reduction for Local Principal Component Analysis
N. Migenda, W. Schenck, in: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2020, pp. 1579–1586.
HSBI-PUB | DOI
 
[22]
2019 | Buchbeitrag | FH-PUB-ID: 1208
Adaptive Dimensionality Adjustment for Online “Principal Component Analysis”
N. Migenda, R. Möller, W. Schenck, in: H. Yin, D. Camacho, P. Tino, A.J. Tallón-Ballesteros, R. Menezes, R. Allmendinger (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2019. 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I, Springer International Publishing, Cham, 2019, pp. 76–84.
HSBI-PUB | DOI
 
[21]
2018 | Buchbeitrag | FH-PUB-ID: 1209
A Case Study on Benchmarking IoT Cloud Services
K. Grünberg, W. Schenck, in: M. Luo, L.-J. Zhang (Eds.), Cloud Computing – CLOUD 2018, Springer International Publishing, Cham, 2018, pp. 398–406.
HSBI-PUB | DOI
 
[20]
2017 | Artikel | FH-PUB-ID: 1210
The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code
S. Kunkel, W. Schenck, Frontiers in Neuroinformatics 11 (2017).
HSBI-PUB | DOI
 
[19]
2017 | Artikel | FH-PUB-ID: 1211
Evaluation and Performance Modeling of a Burst Buffer Solution
W. Schenck, S. El Sayed, M. Foszczynski, W. Homberg, D. Pleiter, ACM SIGOPS Operating Systems Review 50 (2017) 12–26.
HSBI-PUB | DOI
 
[18]
2017 | Buch als Herausgeber | FH-PUB-ID: 1212
Anatomy and Plasticity in Large-Scale Brain Models
M. Butz, W. Schenck, A. van Ooyen, eds., Anatomy and Plasticity in Large-Scale Brain Models, Frontiers Media SA, 2017.
HSBI-PUB | DOI
 
[17]
2017 | Artikel | FH-PUB-ID: 1214
Comparing parallel hardware architectures for visually guided robot navigation
W. Schenck, M. Horst, T. Tiedemann, S. Gaulik, R. Möller, Concurrency and Computation: Practice and Experience 29 (2017).
HSBI-PUB | DOI
 
[16]
2016 | Artikel | FH-PUB-ID: 1213
Editorial: Anatomy and Plasticity in Large-Scale Brain Models
M. Butz, W. Schenck, A. van Ooyen, Frontiers in Neuroanatomy 10 (2016).
HSBI-PUB | DOI
 
[15]
2016 | Buchbeitrag | FH-PUB-ID: 1215
Early Evaluation of the “Infinite Memory Engine” Burst Buffer Solution
W. Schenck, S. El Sayed, M. Foszczynski, W. Homberg, D. Pleiter, in: M. Taufer, B. Mohr, J.M. Kunkel (Eds.), High Performance Computing, Springer International Publishing, Cham, 2016, pp. 604–615.
HSBI-PUB | DOI
 
[14]
2015 | Buchbeitrag | FH-PUB-ID: 1216
Performance Evaluation of Scientific Applications on POWER8
A.V. Adinetz, P.F. Baumeister, H. Böttiger, T. Hater, T. Maurer, D. Pleiter, W. Schenck, S.F. Schifano, in: S.A. Jarvis, S.A. Wright, S.D. Hammond (Eds.), High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, Springer International Publishing, Cham, 2015, pp. 24–45.
HSBI-PUB | DOI
 
[13]
2013 | Artikel | FH-PUB-ID: 1217
Robot studies on saccade-triggered visual prediction
W. Schenck, New Ideas in Psychology 31 (2013) 221–238.
HSBI-PUB | DOI
 
[12]
2013 | Artikel | FH-PUB-ID: 1218
Solving the correspondence problem in stereo vision by internal simulation
A. Kaiser, W. Schenck, R. Möller, Adaptive Behavior 21 (2013) 239–250.
HSBI-PUB | DOI
 
[11]
2012 | Artikel | FH-PUB-ID: 1221
COUPLED SINGULAR VALUE DECOMPOSITION OF A CROSS-COVARIANCE MATRIX
A. KAISER, W. Schenck, R. MÖLLER, International Journal of Neural Systems 20 (2012) 293–318.
HSBI-PUB | DOI
 
[10]
2011 | Artikel | FH-PUB-ID: 1220
Kinematic motor learning
W. Schenck, Connection Science 23 (2011) 239–283.
HSBI-PUB | DOI
 
[9]
2011 | Artikel | FH-PUB-ID: 1219
Grasping of extrafoveal targets: A robotic model
W. Schenck, H. Hoffmann, R. Möller, New Ideas in Psychology 29 (2011) 235–259.
HSBI-PUB | DOI
 
[8]
2009 | Buchbeitrag | FH-PUB-ID: 1222
Space Perception through Visuokinesthetic Prediction
W. Schenck, in: G. Pezzulo, M.V. Butz, O. Sigaud, G. Baldassarre (Eds.), Anticipatory Behavior in Adaptive Learning Systems, Springer Berlin Heidelberg, Berlin, Heidelberg, 2009, pp. 247–266.
HSBI-PUB | DOI
 
[7]
2008 | Artikel | FH-PUB-ID: 1223
Bootstrapping Cognition from Behavior-A Computerized Thought Experiment
R. Möller, W. Schenck, Cognitive Science 32 (2008) 504–542.
HSBI-PUB | DOI
 
[6]
2007 | Artikel | FH-PUB-ID: 1224
Emotion and memory: Event-related potential indices predictive for subsequent successful memory depend on the emotional mood state
M. Kiefer, S. Schuch, W. Schenck, K. Fiedler, Advances in Cognitive Psychology 3 (2007) 363–373.
HSBI-PUB | DOI
 
[5]
2007 | Artikel | FH-PUB-ID: 1225
Spectral contrasts for landmark navigation
T. Kollmeier, F. Röben, W. Schenck, R. Möller, Journal of the Optical Society of America A 24 (2007).
HSBI-PUB | DOI
 
[4]
2007 | Artikel | FH-PUB-ID: 1226
Mood States Modulate Activity in Semantic Brain Areas during Emotional Word Encoding
M. Kiefer, S. Schuch, W. Schenck, K. Fiedler, Cerebral Cortex 17 (2007) 1516–1530.
HSBI-PUB | DOI
 
[3]
2007 | Buchbeitrag | FH-PUB-ID: 1229
Training and Application of a Visual Forward Model for a Robot Camera Head
W. Schenck, R. Möller, in: M.V. Butz, O. Sigaud, G. Pezzulo, G. Baldassarre (Eds.), Anticipatory Behavior in Adaptive Learning Systems, Springer Berlin Heidelberg, Berlin, Heidelberg, 2007, pp. 153–169.
HSBI-PUB | DOI
 
[2]
2005 | Artikel | FH-PUB-ID: 1227
Learning visuomotor transformations for gaze-control and grasping
H. Hoffmann, W. Schenck, R. Möller, Biological Cybernetics 93 (2005) 119–130.
HSBI-PUB | DOI
 
[1]
2005 | Artikel | FH-PUB-ID: 1228
Priming Trait Inferences Through Pictures and Moving Pictures: The Impact of Open and Closed Mindsets.
K. Fiedler, W. Schenck, M. Watling, J.I. Menges, Journal of Personality and Social Psychology 88 (2005) 229–244.
HSBI-PUB | DOI
 
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50 Publikationen

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[50]
2024 | Konferenzbeitrag | FH-PUB-ID: 4699
Technical Readiness of Prescriptive Analytics Platforms: A Survey
M. Niederhaus, N. Migenda, J. Weller, W. Schenck, M. Kohlhase, in: IEEE (Ed.), 2024 35th Conference of Open Innovations Association (FRUCT), IEEE, 2024, pp. 509–519.
HSBI-PUB | DOI
 
[49]
2024 | Artikel | FH-PUB-ID: 4698
NGPCA: Clustering of high-dimensional and non-stationary data streams
N. Migenda, R. Möller, W. Schenck, Software Impacts 20 (2024).
HSBI-PUB | DOI
 
[48]
2024 | Buchbeitrag | FH-PUB-ID: 4915
Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, R. Liu, A. Wegel, S. von Enzberg, M. Kohlhase, W. Schenck, R. Dumitrescu, in: O. Niggemann, J. Beyerer, M. Krantz, C. Kühnert (Eds.), Machine Learning for Cyber-Physical Systems. Selected Papers from the International Conference ML4CPS 2023, Springer Nature Switzerland, Cham, 2024, pp. 89–100.
HSBI-PUB | DOI
 
[47]
2024 | Artikel | FH-PUB-ID: 4913
Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, Y. Naik, T. Heuwinkel, A. Kühn, M. Kohlhase, W. Schenck, R. Dumitrescu, Mathematics 12 (2024).
HSBI-PUB | DOI
 
[46]
2024 | Konferenzbeitrag | FH-PUB-ID: 4644
Exploratory Analysis of Machine Learning Methods for the Prognosis of Falls in Elderly Care Based on Accelerometer Data
L. Klein, C. Ostrau, M. Thies, W. Schenck, U. Rückert, in: D. Salvi, P. Van Gorp, S.A. Shah (Eds.), Pervasive Computing Technologies for Healthcare. 17th EAI International Conference, PervasiveHealth 2023, Malmö, Sweden, November 27-29, 2023, Proceedings, Springer Nature Switzerland, Cham, 2024, pp. 423–437.
HSBI-PUB | DOI
 
[45]
2024 | Artikel | FH-PUB-ID: 4050
Adaptive local Principal Component Analysis improves the clustering of high-dimensional data
N. Migenda, R. Möller, W. Schenck, Pattern Recognition 146 (2024).
HSBI-PUB | DOI
 
[44]
2023 | Konferenzbeitrag | FH-PUB-ID: 4700
Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories
J. Weller, N. Migenda, A. Wegel, M. Kohlhase, W. Schenck, R. Dumitrescu, in: IEEE (Ed.), 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS), IEEE, 2023, pp. 1–7.
HSBI-PUB | DOI
 
[43]
2023 | Konferenzbeitrag | FH-PUB-ID: 4293
Object View Prediction with Aleatoric Uncertainty for Robotic Grasping
C. Schwan, W. Schenck, in: 2023 International Joint Conference on Neural Networks (IJCNN), IEEE, 2023, pp. 1–8.
HSBI-PUB | DOI
 
[42]
2023 | Artikel | FH-PUB-ID: 2774 | OA
A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions
A. Tharwat, W. Schenck, Mathematics 11 (2023).
HSBI-PUB | DOI | Download (ext.)
 
[41]
2023 | Artikel | FH-PUB-ID: 3453 | OA
sEMG-based prediction of human forearm movements utilizing a biomechanical model based on individual anatomical/ physiological measures and a reduced set of optimization parameters
N. Grimmelsmann, M. Mechtenberg, W. Schenck, H.G. Meyer, A. Schneider, PLOS ONE 18 (2023).
HSBI-PUB | DOI | Download (ext.)
 
[40]
2022 | Artikel | FH-PUB-ID: 1799 | OA
Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks
K. Vandevoorde, L. Vollenkemper, C. Schwan, M. Kohlhase, W. Schenck, Sensors 22 (2022).
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[39]
2022 | Konferenzbeitrag | FH-PUB-ID: 2945
Impact of different loss functions on denoising of microscopic images
Z.H. Shah, M. Muller, B. Hammer, T. Huser, W. Schenck, in: 2022 International Joint Conference on Neural Networks (IJCNN), IEEE, 2022, pp. 1–10.
HSBI-PUB | DOI
 
[38]
2022 | Artikel | FH-PUB-ID: 2944 | OA
Open set task augmentation facilitates generalization of deep neural networks trained on small data sets
W. Zai El Amri, F. Reinhart, W. Schenck, Neural Computing and Applications 34 (2022) 6067–6083.
HSBI-PUB | DOI | Download (ext.)
 
[37]
2022 | Konferenzbeitrag | FH-PUB-ID: 2776 | OA
Design of Interpretable Machine Learning Tasks for the Application to Industrial Order Picking
C. Schwan, W. Schenck, in: J. Jasperneite, V. Lohweg (Eds.), Kommunikation und Bildverarbeitung in der Automation. Ausgewählte Beiträge der Jahreskolloquien KommA und BVAu 2020, Springer Berlin Heidelberg, Berlin, Heidelberg, 2022, pp. 291–303.
HSBI-PUB | DOI | Download (ext.)
 
[36]
2022 | Artikel | FH-PUB-ID: 2775 | OA
A Novel Low-Query-Budget Active Learner with Pseudo-Labels for Imbalanced Data
A. Tharwat, W. Schenck, Mathematics 10 (2022).
HSBI-PUB | DOI | Download (ext.)
 
[35]
2022 | Konferenzbeitrag | FH-PUB-ID: 2569
Collaborative System for Question Answering in German Case Law Documents
C. Hoppe, N. Migenda, D. Pelkmann, D.A. Hötte, W. Schenck, in: L.M. Camarinha-Matos, A. Ortiz, X. Boucher, A.L. Osório (Eds.), Collaborative Networks in Digitalization and Society 5.0, Springer International Publishing, Cham, 2022, pp. 303–312.
HSBI-PUB | DOI
 
[34]
2021 | Artikel | FH-PUB-ID: 1202
A conceptual and practical comparison of PSO-style optimization algorithms
A. Tharwat, W. Schenck, Expert Systems with Applications 167 (2021).
HSBI-PUB | DOI
 
[33]
2021 | Artikel | FH-PUB-ID: 1201 | OA
Deep-learning based denoising and reconstruction of super-resolution structured illumination microscopy images
Z.H. Shah, M. Müller, T.-C. Wang, P.M. Scheidig, A. Schneider, M. Schüttpelz, T. Huser, W. Schenck, Photonics Research 9 (2021).
HSBI-PUB | DOI | Download (ext.)
 
[32]
2021 | Konferenzbeitrag | FH-PUB-ID: 2570
Towards Intelligent Legal Advisors for Document Retrieval and Question-Answering in German Legal Documents
C. Hoppe, D. Pelkmann, N. Migenda, D.A. Hotte, W. Schenck, in: 2021 IEEE Fourth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), IEEE, 2021, pp. 29–32.
HSBI-PUB | DOI
 
[31]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Advanced Data Analytics Platform for Manufacturing Companies
T. Voigt, N. Migenda, M. Schöne, D. Pelkmann, M. Fricke, W. Schenck, M. Kohlhase, in: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, pp. 01–08.
HSBI-PUB | DOI
 
[30]
2021 | Konferenzbeitrag | FH-PUB-ID: 2572
Variational Autoencoder based Novelty Detection for Real-World Time Series
L. Steinmann, N. Migenda, T. Voigt, M. Kohlhase, W. Schenck, in: 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, New York, NY, USA, 2021, pp. 1–7.
HSBI-PUB | DOI
 
[29]
2021 | Artikel | FH-PUB-ID: 1203
Adaptive dimensionality reduction for neural network-based online principal component analysis
N. Migenda, R. Möller, W. Schenck, PLOS ONE 16 (2021).
HSBI-PUB | DOI
 
[28]
2021 | Artikel | FH-PUB-ID: 2777
Population initialization techniques for evolutionary algorithms for single-objective constrained optimization problems: Deterministic vs. stochastic techniques
A. Tharwat, W. Schenck, Swarm and Evolutionary Computation 67 (2021).
HSBI-PUB | DOI
 
[27]
2020 | Artikel | FH-PUB-ID: 1204
Balancing Exploration and Exploitation: A novel active learner for imbalanced data
A. Tharwat, W. Schenck, Knowledge-Based Systems 210 (2020).
HSBI-PUB | DOI
 
[26]
2020 | Konferenzbeitrag | FH-PUB-ID: 1206
How to Label? Combining Experts’ Knowledge for German Text Classification
D. Pelkmann, A. Tharwat, W. Schenck, in: 2020 7th Swiss Conference on Data Science (SDS), IEEE, 2020, pp. 61–62.
HSBI-PUB | DOI
 
[25]
2020 | Konferenzbeitrag | FH-PUB-ID: 1207
Visual Movement Prediction for Stable Grasp Point Detection
C. Schwan, W. Schenck, in: L. Iliadis, P.P. Angelov, C. Jayne, E. Pimenidis (Eds.), Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. Proceedings of the EANN 2020, Springer International Publishing, Cham, 2020, pp. 70–81.
HSBI-PUB | DOI
 
[24]
2020 | Diskussionspapier | FH-PUB-ID: 2778 | OA
Deep-learning based denoising and reconstruction of super-resolution structured illumination microscopy images
Z.H. Shah, M. Müller, T.-C. Wang, P.M. Scheidig, A. Schneider, M. Schüttpelz, T. Huser, W. Schenck, Deep-Learning Based Denoising and Reconstruction of Super-Resolution Structured Illumination Microscopy Images, Cold Spring Harbor Laboratory, 2020.
HSBI-PUB | DOI | Download (ext.)
 
[23]
2020 | Konferenzbeitrag | FH-PUB-ID: 2574
Adaptive Dimensionality Reduction for Local Principal Component Analysis
N. Migenda, W. Schenck, in: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2020, pp. 1579–1586.
HSBI-PUB | DOI
 
[22]
2019 | Buchbeitrag | FH-PUB-ID: 1208
Adaptive Dimensionality Adjustment for Online “Principal Component Analysis”
N. Migenda, R. Möller, W. Schenck, in: H. Yin, D. Camacho, P. Tino, A.J. Tallón-Ballesteros, R. Menezes, R. Allmendinger (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2019. 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I, Springer International Publishing, Cham, 2019, pp. 76–84.
HSBI-PUB | DOI
 
[21]
2018 | Buchbeitrag | FH-PUB-ID: 1209
A Case Study on Benchmarking IoT Cloud Services
K. Grünberg, W. Schenck, in: M. Luo, L.-J. Zhang (Eds.), Cloud Computing – CLOUD 2018, Springer International Publishing, Cham, 2018, pp. 398–406.
HSBI-PUB | DOI
 
[20]
2017 | Artikel | FH-PUB-ID: 1210
The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code
S. Kunkel, W. Schenck, Frontiers in Neuroinformatics 11 (2017).
HSBI-PUB | DOI
 
[19]
2017 | Artikel | FH-PUB-ID: 1211
Evaluation and Performance Modeling of a Burst Buffer Solution
W. Schenck, S. El Sayed, M. Foszczynski, W. Homberg, D. Pleiter, ACM SIGOPS Operating Systems Review 50 (2017) 12–26.
HSBI-PUB | DOI
 
[18]
2017 | Buch als Herausgeber | FH-PUB-ID: 1212
Anatomy and Plasticity in Large-Scale Brain Models
M. Butz, W. Schenck, A. van Ooyen, eds., Anatomy and Plasticity in Large-Scale Brain Models, Frontiers Media SA, 2017.
HSBI-PUB | DOI
 
[17]
2017 | Artikel | FH-PUB-ID: 1214
Comparing parallel hardware architectures for visually guided robot navigation
W. Schenck, M. Horst, T. Tiedemann, S. Gaulik, R. Möller, Concurrency and Computation: Practice and Experience 29 (2017).
HSBI-PUB | DOI
 
[16]
2016 | Artikel | FH-PUB-ID: 1213
Editorial: Anatomy and Plasticity in Large-Scale Brain Models
M. Butz, W. Schenck, A. van Ooyen, Frontiers in Neuroanatomy 10 (2016).
HSBI-PUB | DOI
 
[15]
2016 | Buchbeitrag | FH-PUB-ID: 1215
Early Evaluation of the “Infinite Memory Engine” Burst Buffer Solution
W. Schenck, S. El Sayed, M. Foszczynski, W. Homberg, D. Pleiter, in: M. Taufer, B. Mohr, J.M. Kunkel (Eds.), High Performance Computing, Springer International Publishing, Cham, 2016, pp. 604–615.
HSBI-PUB | DOI
 
[14]
2015 | Buchbeitrag | FH-PUB-ID: 1216
Performance Evaluation of Scientific Applications on POWER8
A.V. Adinetz, P.F. Baumeister, H. Böttiger, T. Hater, T. Maurer, D. Pleiter, W. Schenck, S.F. Schifano, in: S.A. Jarvis, S.A. Wright, S.D. Hammond (Eds.), High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, Springer International Publishing, Cham, 2015, pp. 24–45.
HSBI-PUB | DOI
 
[13]
2013 | Artikel | FH-PUB-ID: 1217
Robot studies on saccade-triggered visual prediction
W. Schenck, New Ideas in Psychology 31 (2013) 221–238.
HSBI-PUB | DOI
 
[12]
2013 | Artikel | FH-PUB-ID: 1218
Solving the correspondence problem in stereo vision by internal simulation
A. Kaiser, W. Schenck, R. Möller, Adaptive Behavior 21 (2013) 239–250.
HSBI-PUB | DOI
 
[11]
2012 | Artikel | FH-PUB-ID: 1221
COUPLED SINGULAR VALUE DECOMPOSITION OF A CROSS-COVARIANCE MATRIX
A. KAISER, W. Schenck, R. MÖLLER, International Journal of Neural Systems 20 (2012) 293–318.
HSBI-PUB | DOI
 
[10]
2011 | Artikel | FH-PUB-ID: 1220
Kinematic motor learning
W. Schenck, Connection Science 23 (2011) 239–283.
HSBI-PUB | DOI
 
[9]
2011 | Artikel | FH-PUB-ID: 1219
Grasping of extrafoveal targets: A robotic model
W. Schenck, H. Hoffmann, R. Möller, New Ideas in Psychology 29 (2011) 235–259.
HSBI-PUB | DOI
 
[8]
2009 | Buchbeitrag | FH-PUB-ID: 1222
Space Perception through Visuokinesthetic Prediction
W. Schenck, in: G. Pezzulo, M.V. Butz, O. Sigaud, G. Baldassarre (Eds.), Anticipatory Behavior in Adaptive Learning Systems, Springer Berlin Heidelberg, Berlin, Heidelberg, 2009, pp. 247–266.
HSBI-PUB | DOI
 
[7]
2008 | Artikel | FH-PUB-ID: 1223
Bootstrapping Cognition from Behavior-A Computerized Thought Experiment
R. Möller, W. Schenck, Cognitive Science 32 (2008) 504–542.
HSBI-PUB | DOI
 
[6]
2007 | Artikel | FH-PUB-ID: 1224
Emotion and memory: Event-related potential indices predictive for subsequent successful memory depend on the emotional mood state
M. Kiefer, S. Schuch, W. Schenck, K. Fiedler, Advances in Cognitive Psychology 3 (2007) 363–373.
HSBI-PUB | DOI
 
[5]
2007 | Artikel | FH-PUB-ID: 1225
Spectral contrasts for landmark navigation
T. Kollmeier, F. Röben, W. Schenck, R. Möller, Journal of the Optical Society of America A 24 (2007).
HSBI-PUB | DOI
 
[4]
2007 | Artikel | FH-PUB-ID: 1226
Mood States Modulate Activity in Semantic Brain Areas during Emotional Word Encoding
M. Kiefer, S. Schuch, W. Schenck, K. Fiedler, Cerebral Cortex 17 (2007) 1516–1530.
HSBI-PUB | DOI
 
[3]
2007 | Buchbeitrag | FH-PUB-ID: 1229
Training and Application of a Visual Forward Model for a Robot Camera Head
W. Schenck, R. Möller, in: M.V. Butz, O. Sigaud, G. Pezzulo, G. Baldassarre (Eds.), Anticipatory Behavior in Adaptive Learning Systems, Springer Berlin Heidelberg, Berlin, Heidelberg, 2007, pp. 153–169.
HSBI-PUB | DOI
 
[2]
2005 | Artikel | FH-PUB-ID: 1227
Learning visuomotor transformations for gaze-control and grasping
H. Hoffmann, W. Schenck, R. Möller, Biological Cybernetics 93 (2005) 119–130.
HSBI-PUB | DOI
 
[1]
2005 | Artikel | FH-PUB-ID: 1228
Priming Trait Inferences Through Pictures and Moving Pictures: The Impact of Open and Closed Mindsets.
K. Fiedler, W. Schenck, M. Watling, J.I. Menges, Journal of Personality and Social Psychology 88 (2005) 229–244.
HSBI-PUB | DOI
 
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