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ORCIDBernd Waschneck
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2020 – today
- 2024
[j5]Max Sponner
, Lorenzo Servadei, Bernd Waschneck, Robert Wille, Akash Kumar:
Leveraging Temporal Patterns: Automated Augmentation to Create Temporal Early Exit Networks for Efficient Edge AI. IEEE Access 12: 169787-169804 (2024)- [j4]Max Sponner, Bernd Waschneck, Akash Kumar:
Adapting Neural Networks at Runtime: Current Trends in At-Runtime Optimizations for Deep Learning. ACM Comput. Surv. 56(10): 248 (2024) - [j3]Eslam Hussein, Bernd Waschneck, Christian Mayr:
Automating application-driven customization of ASIPs: A survey. J. Syst. Archit. 148: 103080 (2024) - [j2]Elias Trommer, Bernd Waschneck, Akash Kumar:
Smaller Together: Groupwise Encoding of Sparse Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(12): 4476-4489 (2024) - [c13]Max Sponner, Lorenzo Servadei, Bernd Waschneck, Robert Wille, Akash Kumar:
Harnessing Temporal Information for Efficient Edge AI. FMEC 2024: 5-13 - [c12]Max Sponner, Lorenzo Servadei, Bernd Waschneck, Robert Wille, Akash Kumar:
Efficient Post-training Augmentation for Adaptive Inference in Heterogeneous and Distributed IoT Environments. SAMOS 2024: 99-108 - [i9]Max Sponner, Lorenzo Servadei, Bernd Waschneck, Robert Wille, Akash Kumar:
Efficient Post-Training Augmentation for Adaptive Inference in Heterogeneous and Distributed IoT Environments. CoRR abs/2403.07957 (2024) - [i8]Max Sponner, Lorenzo Servadei, Bernd Waschneck, Robert Wille, Akash Kumar:
Temporal Decisions: Leveraging Temporal Correlation for Efficient Decisions in Early Exit Neural Networks. CoRR abs/2403.07958 (2024) - [i7]Elias Trommer, Bernd Waschneck, Akash Kumar:
QoS-Nets: Adaptive Approximate Neural Network Inference. CoRR abs/2410.07762 (2024) - 2023
- [c11]Elias Trommer, Bernd Waschneck, Akash Kumar:
High-Throughput Approximate Multiplication Models in PyTorch. DDECS 2023: 79-82 - [i6]Max Sponner, Julius Ott, Lorenzo Servadei, Bernd Waschneck, Robert Wille, Akash Kumar:
Temporal Patience: Efficient Adaptive Deep Learning for Embedded Radar Data Processing. CoRR abs/2309.05686 (2023) - 2022
- [j1]Binyi Wu, Bernd Waschneck, Christian Georg Mayr:
Convolutional Neural Networks Quantization with Double-Stage Squeeze-and-Threshold. Int. J. Neural Syst. 32(12): 2250051:1-2250051:13 (2022) - [c10]Binyi Wu, Wolfgang Furtner, Bernd Waschneck, Christian Mayr:
Industry-track: Towards Agile Design of Neural Processing Unit. CODES+ISSS 2022: 17-20 - [c9]Binyi Wu, Bernd Waschneck, Christian Mayr:
Neural Architecture Search for Low-Precision Neural Networks. ICANN (4) 2022: 743-755 - [c8]Elias Trommer, Bernd Waschneck, Akash Kumar:
Combining Gradients and Probabilities for Heterogeneous Approximation of Neural Networks. ICCAD 2022: 150:1-150:8 - [c7]Binyi Wu, Wolfgang Furtner, Bernd Waschneck, Christian Mayr:
Prototyping of Low-Cost Configurable Sparse Neural Processing Unit with Buffer and Mixed-Precision Reshapeable MAC Array. ICPADS 2022: 712-719 - [c6]Tim Langer, Bernd Waschneck, Johannes Partzsch, Florian Kelber, Christian Mayr:
Hardware-Efficient Ultrasonic Entrance Counting: Comparing Different Machine Learning Approaches. ICPR 2022: 755-761 - [i5]Elias Trommer, Bernd Waschneck, Akash Kumar:
Combining Gradients and Probabilities for Heterogeneous Approximation of Neural Networks. CoRR abs/2208.07265 (2022) - [i4]Binyi Wu, Bernd Waschneck, Christian Georg Mayr:
Convolutional Neural Networks Quantization with Attention. CoRR abs/2209.15317 (2022) - 2021
- [c5]Binyi Wu, Bernd Waschneck, Christian Mayr:
Squeeze-and-Threshold Based Quantization for Low-Precision Neural Networks. EANN 2021: 232-243 - [c4]Elias Trommer, Bernd Waschneck, Akash Kumar:
dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference. ICCAD 2021: 1-9 - [i3]Max Sponner, Bernd Waschneck, Akash Kumar:
Compiler Toolchains for Deep Learning Workloads on Embedded Platforms. CoRR abs/2104.04576 (2021) - [i2]Elias Trommer, Bernd Waschneck, Akash Kumar:
dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference. CoRR abs/2111.12345 (2021) - 2020
- [b1]Bernd Waschneck:
Autonome Entscheidungsfindung in der Produktionssteuerung komplexer Werkstattfertigungen. University of Stuttgart, Germany, Fraunhofer Verlag 2020, ISBN 978-3-8396-1623-9, pp. 1-230 - [c3]Simon Mittermaier, Ludwig Kürzinger, Bernd Waschneck, Gerhard Rigoll:
Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-Convolutions. ICASSP 2020: 7454-7458
2010 – 2019
- 2019
- [i1]Simon Mittermaier, Ludwig Kürzinger, Bernd Waschneck, Gerhard Rigoll:
Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-Convolutions. CoRR abs/1911.02086 (2019) - 2018
- [c2]Bernd Waschneck, Thomas Altenmüller, Thomas Bauernhansl, Andreas Kyek:
Case Study on Operator Compliance to Scheduling Decisions in Semiconductor Manufacturing. CASE 2018: 649-652 - 2016
- [c1]Bernd Waschneck, Thomas Altenmüller, Thomas Bauernhansl, Andreas Kyek:
Production Scheduling in Complex Job Shops from an Industry 4.0 Perspective: A Review and Challenges in the Semiconductor Industry. SAMI@iKNOW 2016
Coauthor Index
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