Lehrstuhl für Allgemeine Elektrotechnik und Theoretische Nachrichtentechnik
Prof. Dr.- Ing. Anton Kummert
Publikationen
| 363. |
Nonlinear Circuit Simulation by Means of Alfred Fettweis' Wave Digital Principles
IEEE Circuits and Systems Magazine,
19(1):55-C3
2019
ISSN: 1531-636X
Schlüsselwörter: circuit simulation;nonlinear network analysis;wave digital filters;Alfred Fettweis wave digital principles;general circuit simulation strategy;digital filter design;analogue reference circuits;accurate digital model;WDFs;Wave Digital Filters;commercial circuit design;dependable circuit simulation;nonlinear circuit simulation;Digital filters;Circuit simulation;Circuit synthesis;Finite element analysis;Nonlinear circuits;SPICE |
| 362. |
Fast and Reliable Architecture Selection for Convolutional Neural Networks
Proceedings of the 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pages 179-184, Bruges 2019
ArXiv,
abs/1905.01924
2019
Schlüsselwörter: Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG) Zusammenfassung: The performance of a Convolutional Neural Network (CNN) depends on its hyperparameters, like the number of layers, kernel sizes, or the learning rate for example. Especially in smaller networks and applications with limited computational resources, optimisation is key. We present a fast and efficient approach for CNN architecture selection. Taking into account time consumption, precision and robustness, we develop a heuristic to quickly and reliably assess a network's performance. In combination with Bayesian optimisation (BO), to effectively cover the vast parameter space, our contribution offers a plain and powerful architecture search for this machine learning technique. |
| 361. |
Spoken Letter Recognition using Deep Convolutional Neural Networks on Sparse and Dissimilar Data
2019 IEEE International Symposium on Circuits and Systems (ISCAS)
, Seite 1-5.
2019
Schlüsselwörter: Training;Task analysis;Visualization;Spectrogram;Convolutional neural networks;Image recognition |
| 360. |
Automatic Labeling of Industrial Images by using Generative Adversarial Networks
2019 IEEE International Symposium on Circuits and Systems (ISCAS)
, Seite 1-5.
2019
Schlüsselwörter: Kernel;Generative adversarial networks;Training;Decoding;Generators;Loss measurement;Mutual information |
| 359. |
Live Demonstration: A Raspberry Pi Based Video Pipeline for 2-D Wave Digital Filters on Low-Cost FPGA Hardware
2019 IEEE International Symposium on Circuits and Systems (ISCAS)
, Seite 1-1.
2019
Schlüsselwörter: Field programmable gate arrays;Economic indicators;Liquid crystal displays;Pipeline processing;Digital filters;Hardware;Universal Serial Bus;Wave Digital Filter;Video Pipeline;FPGA;Raspberry Pi |
| 358. |
A Raspberry Pi Based Video Pipeline for 2-D Wave Digital Filters on Low-Cost FPGA Hardware
2019 IEEE International Symposium on Circuits and Systems (ISCAS)
, Seite 1-5.
2019
Schlüsselwörter: Field programmable gate arrays;Streaming media;Pipelines;Economic indicators;Universal Serial Bus;Hardware;Digital filters;Wave Digital Filter;Video Pipeline;FPGA;Raspberry Pi |
| 357. |
Multi-View Fusion Neural Network with Application in the Manufacturing Industry
2019 IEEE International Symposium on Circuits and Systems (ISCAS)
, Seite 1-5.
2019
Schlüsselwörter: Cameras;Cavity resonators;Biological neural networks;Training;Predictive models;Convolutional neural networks |
| 356. |
False Alarm Reduction for Active Sonars using Deep Learning Architectures
2019 UDT, Stockholm
2019
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