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2020 – today
- 2023
[b1]Cecilia Latotzke:
Co-optimization of neural networks and hardware architectures for their efficient execution. RWTH Aachen University, Germany, 2023- [c6]Cecilia Latotzke, Amarin Kloeker, Simon Schoening, Fabian Kemper, Mazen Slimi, Lutz Eckstein, Tobias Gemmeke:
FPGA-based Acceleration of Lidar Point Cloud Processing and Detection on the Edge. IV 2023: 1-8 - [c5]Mikail Yayla
, Cecilia Latotzke, Robert Huber, Somar Iskif, Tobias Gemmeke, Jian-Jia Chen:
DAEBI: A Tool for Data Flow and Architecture Explorations of Binary Neural Network Accelerators. SAMOS 2023: 107-122 - 2022
- [c4]Cecilia Latotzke, Tim Ciesielski, Tobias Gemmeke:
Design of High-Throughput Mixed-Precision CNN Accelerators on FPGA. FPL 2022: 358-365 - [c3]Cecilia Latotzke, Batuhan Balim, Tobias Gemmeke:
Post-Training Quantization for Energy Efficient Realization of Deep Neural Networks. ICMLA 2022: 1559-1566 - [i3]Cecilia Latotzke, Tim Ciesielski, Tobias Gemmeke:
Design of High-Throughput Mixed-Precision CNN Accelerators on FPGA. CoRR abs/2208.04854 (2022) - [i2]Cecilia Latotzke, Batuhan Balim, Tobias Gemmeke:
Post-Training Quantization for Energy Efficient Realization of Deep Neural Networks. CoRR abs/2210.07906 (2022) - 2021
- [j1]Cecilia Latotzke, Tobias Gemmeke:
Efficiency Versus Accuracy: A Review of Design Techniques for DNN Hardware Accelerators. IEEE Access 9: 9785-9799 (2021) - [c2]Cecilia Latotzke, Johnson Loh, Tobias Gemmeke:
Cascaded Classifier for Pareto-Optimal Accuracy-Cost Trade-Off Using Off-the-Shelf ANNs. LOD 2021: 423-435 - [i1]Cecilia Latotzke, Johnson Loh, Tobias Gemmeke:
Cascaded Classifier for Pareto-Optimal Accuracy-Cost Trade-Off Using off-the-Shelf ANNs. CoRR abs/2110.14256 (2021) - 2020
- [c1]Tim Stadtmann, Cecilia Latotzke, Tobias Gemmeke:
From Quantitative Analysis to Synthesis of Efficient Binary Neural Networks. ICMLA 2020: 93-100
Coauthor Index
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