no code implementations • 21 Apr 2014 • Adam H. Marblestone, Evan R Daugharthy, Reza Kalhor, Ian D Peikon, Justus M Kebschull, Seth L Shipman, Yuriy Mishchenko, Je Hyuk Lee, Konrad P. Kording, Edward S. Boyden, Anthony M Zador, George M. Church
We propose a neural connectomics strategy called Fluorescent In-Situ Sequencing of Barcoded Individual Neuronal Connections (FISSEQ-BOINC), leveraging fluorescent in situ nucleic acid sequencing in fixed tissue (FISSEQ).
Neurons and Cognition
no code implementations • 19 Oct 2018 • Yuriy Mishchenko, Yusuf Goren, Ming Sun, Chris Beauchene, Spyros Matsoukas, Oleg Rybakov, Shiv Naga Prasad Vitaladevuni
We investigate low-bit quantization to reduce computational cost of deep neural network (DNN) based keyword spotting (KWS).
no code implementations • 9 Aug 2020 • Christin Jose, Yuriy Mishchenko, Thibaud Senechal, Anish Shah, Alex Escott, Shiv Vitaladevuni
In this paper, we propose two new methods for detecting the endpoints of wake words in neural KWS that use single-stage word-level neural networks.
no code implementations • 13 Oct 2020 • Yixin Gao, Yuriy Mishchenko, Anish Shah, Spyros Matsoukas, Shiv Vitaladevuni
Wake word (WW) spotting is challenging in far-field not only because of the interference in signal transmission but also the complexity in acoustic environments.
no code implementations • 15 Jun 2022 • Christin Jose, Joseph Wang, Grant P. Strimel, Mohammad Omar Khursheed, Yuriy Mishchenko, Brian Kulis
We also show that when our approach is used in conjunction with a max-pooling loss, we are able to improve relative false accepts by 25 % at a fixed latency when compared to cross entropy loss.