Deep Learning - Training

Check out this collection of posters to see how researchers are training with deep learning and are accelerating their work with the power of GPUs.

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    An improvement of neural network accuracy by distributed learning

    Konstantin Kuznetsov, deeplearning architect, Entropix

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    Deep Learning for Targeted Assimilation of Satellite Data

    Yu-Ju Lee, Professional Research Assistant, University of Colorado Boulder

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    Hybrid Learning Network : A Novel Architecture for Fast Learning

    Ying Liu, Professor, University of Chinese Academy of Sciences

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    Model Quantization Based On Training

    Yafei Lv, researcher, IFLYTEK CO.,LTD.

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    Deep Learning with Very Large Models on POWER9 Systems with Volta GPUs

    Saritha Vinod, Senior Software Engineer, IBM

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    Classification of Animals Based on their Species Using Deep Learning Framework

    Satyadhyan Chickerur, Professor, K L E Technological University

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    Automatic Speech Recognition for Low-resource Manipuri Language

    Tanvina Patel, Data Scientist (Speech Systems), Cogknit Semantics

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    Deep Clean: GPU Powered Speech Denoising using Adversarial Learning

    Laxmi Pandey, Research Engineer, Cogknit Semantics

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    Online Learning for Speaker-Adaptive Language Models

    Chih Hu, PhD Student, Carnegie Mellon University

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    Auto-ML for Automated Optimization of Speech Recognition on Mobile Devices

    Akshay Chandrashekaran, PhD. Candidate, Carnegie Mellon University

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    Speaker Role Contextual Modeling for Spoken Language Understanding in Dialogues

    Shang-Yu Su, student, National Taiwan University

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    LangDectNet: Spoken Language Detection Using Parallelly Trainable Deep RCNN Architectures.

    Shivam Patel, Research Student, Nirma University