1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.SD2023
Deep learning-based denoising streamed from mobile phones improves speech-in-noise understanding for hearing aid users
Peter Udo Diehl, Hannes Zilly, Felix Sattler +11
The hearing loss of almost half a billion people is commonly treated with hearing aids. However, current hearing aids often do not work well in real-world noisy environments. We pr…
cs.LG2020★ 1 cited
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training
Simon Wiedemann, Temesgen Mehari, Kevin Kepp +1
Deep Neural Networks are successful but highly computationally expensive learning systems. One of the main sources of time and energy drains is the well known backpropagation (back…