Sound event detection with binary neural networks on tightly power-constrained IoT devices-Reference-Cited by-同舟云学术

Sound event detection with binary neural networks on tightly power-constrained IoT devices

Published:2020-08-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design
language:
Short-container-title:

Author:

Cerutti Gianmarco¹,Andri Renzo¹,Cavigelli Lukas¹,Farella Elisabetta²,Magno Michele¹,Benini Luca³

Affiliation:

1. ETH Zurich, Zurich, Switzerland

2. Fondazione Bruno Kessler, Trento, Italy

3. ETH Zurich, Zurich, Switzerland and University of Bologna, Bologna, Italy

Funder

U.S. Office of Naval Research

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3370748.3406588

Reference42 articles.

1. Gianmarco Cerutti et al. 2020. Compact recurrent neural networks for acoustic event detection on low-energy low-complexity platforms. IEEE JSTSP (2020). Gianmarco Cerutti et al. 2020. Compact recurrent neural networks for acoustic event detection on low-energy low-complexity platforms. IEEE JSTSP (2020).

2. Matthieu Courbariaux et al. 2016. Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1. In arXiv:1602.02830. Matthieu Courbariaux et al. 2016. Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1. In arXiv:1602.02830.

Cited by 21 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CBin-NN: An Inference Engine for Binarized Neural Networks;Electronics;2024-04-24

2. “It os Okay to be Uncommon”: Quantizing Sound Event Detection Networks on Hardware Accelerators with Uncommon Sub-Byte Support;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Implementation of 32-Bit Ripple Carry Adder using Binary Neural Networks for Ultra Low-Power Applications;2023 IEEE 3rd International Conference on Smart Technologies for Power, Energy and Control (STPEC);2023-12-10

4. Enhancing Lightweight Neural Networks for Small Object Detection in IoT Applications;2023 IEEE SENSORS;2023-10-29

5. Securing Tiny Transformer-Based Computer Vision Models: Evaluating Real-World Patch Attacks;2023 IEEE 9th World Forum on Internet of Things (WF-IoT);2023-10-12