Výsledky vyhledávání - "Ouais Alsharif"

Streaming Object Detection for 3-D Point Clouds

Autor: Zhengdong Zhang, Ouais Alsharif, Benjamin Caine, Brandon Yang, Zhifeng Chen, Jonathon Shlens, Christoph Sprunk, Vijay K. Vasudevan, Jiquan Ngiam, Wei Han

Publikováno v: Computer Vision – ECCV 2020 ISBN: 9783030585228
ECCV (18)

Autonomous vehicles operate in a dynamic environment, where the speed with which a vehicle can perceive and react impacts the safety and efficacy of the system. LiDAR provides a prominent sensory modality that informs many existing perceptual systems

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::aa3422eb4646307fb17b24a46cdd6126
https://doi.org/10.1007/978-3-030-58523-5_25

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Personalized speech recognition on mobile devices

Autor: Raziel Alvarez, Francoise Beaufays, Rohit Prabhavalkar, Alexander H. Gruenstein, Kanishka Rao, Carolina Parada, Ian McGraw, David Rybach, Ouais Alsharif, Montse Gonzalez Arenas, Hasim Sak

Publikováno v: ICASSP

We describe a large vocabulary speech recognition system that is accurate, has low latency, and yet has a small enough memory and computational footprint to run faster than real-time on a Nexus 5 Android smartphone. We employ a quantized Long Short-T

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dae983dd89cc96eaf0287640b8ced70d
https://doi.org/10.1109/icassp.2016.7472820

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On the Compression of Recurrent Neural Networks with an Application to LVCSR acoustic modeling for Embedded Speech Recognition

Autor: Rohit Prabhavalkar, Ouais Alsharif, Antoine Bruguier, Lan McGraw

Publikováno v: ICASSP

We study the problem of compressing recurrent neural networks (RNNs). In particular, we focus on the compression of RNN acoustic models, which are motivated by the goal of building compact and accurate speech recognition systems which can be run effi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1924e316c71c939d49f298208b0087b

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Long short term memory neural network for keyboard gesture decoding

Autor: Tom Ouyang, Ouais Alsharif, Shumin Zhai, Francoise Beaufays, Johan Schalkwyk, Thomas M. Breuel

Publikováno v: ICASSP

Gesture typing is an efficient input method for phones and tablets using continuous traces created by a pointed object (e.g., finger or stylus). Translating such continuous gestures into textual input is a challenging task as gesture inputs exhibit m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4d9e923cb06e6935c0cd640787d954e3
https://doi.org/10.1109/icassp.2015.7178336

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