SILICON VALLEY 26-29 MAR 2018
Home > Resources: GTC 2017 Posters > Deep Learning And Artificial Intelligence

Deep Learning And Artificial Intelligence

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

 
  •  

    A Distributed Deep Learning Platform - BlueMind

    Zhiwen Fu, Software Engineer, IBM China Systems Lab

  •  

    Assessing the Applicability of Deep Learning Techniques in Computer Assisted Radiology for Diagnosing Tendons

    Norbert Kapinski, Visual Analysis Specialist, Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw

  •  

    Column Weight Pruning for Accelerating DNN Inferences

    Yasumoto Tomita, Research Manager, Fujitsu Laboratories LTD.

  •  

    End-to-End Task-Oriented Neural Dialogue System

    Yun-Nung Chen, Assistant Professor, National Taiwan University

  •  

    GPU Based Acceleration of Facial Emotion Detection Using Machine Learning

    Dr Nagendra Gajjar , (Professor & PG Coordinator (Embedded Systems), Institute of Technology, Nirma University S.G. Highway, Ahmedabad 382481 Gujarat, INDIA)

  •  

    GPU Processing Accelerates Training Autoencoders for Bird Sounds Data

    Jian Guo, PhD Student, Tokyo Institute of Technology

  •  

    High-Performance Data Loading and Augmentation for Deep Neural Network Training

    Trevor Gale, Research Intern, Samsung Research America

  •  

    Identifying Spatiotemporal Dynamics of Brain Function Using Deep Learning NVIDIA-Docker Containers

    Zachary Harper, Research Associate, Medical College of Wisconsin

  •  

    Learning Users to Improve User Experience: Detecting Relevance from Biometrics

    Christopher Chow, PhD Student, The Australian National University

  •  

    LonchaNet: A Slice-based CNN Architecture for Real-time 3D Object Recognition

    Alberto Garcia Garcia, PhD Student, University of Alicante

  •  

    Massively Parallel Gradient Boosting With XGBoost

    Rory Mitchell, Student, Waikato University

  •  

    Multi-GPU Implementation for Automatic Segmentation of Brachial Plexus Ultrasonic Image

    Yan Songlin, Student, Computer Network Information Center, Chinese Academy of Sciences

  •  

    Music Generation From Raw Audio

    Vasanth kalingeri, Graduate student, University of Massachusetts Amherst

  •  

    NU-LiteNet: Mobile Landmark Recognition Using Convolutional Neural Networks

    Paisarn Muneesawang, Associate professor, Naresuan University

  •  

    PowerAI on IBM Systems with GPUs - Where Strength Meets Strength

    Anto Ajay Raj John, Advisory Software Engineer, IBM

  •  

    Precision and Recall Study in Deep Learning

    Wu Bao, C/C++ engineer, Yaspeed

  •  

    Predicting Probabilistic Parameters of a Large-Scale Asynchronous SGD Deep Learning System

    Yosuke Oyama, Student, Tokyo Institute of Technology

  •  

    Telepresence Android Imbuned With Deep Learning

    Ali Lemus, Director of Turing Laboratory, Galileo University

  •  

    Deep Learning Data Augmentation in GPU

    Heverton Sarah, Student, UFF

  •  

    Memory Reduction Method for Training Very Deep Neural Networks on a GPU

    Koichi Shirahata, Researcher, FUJITSU LABORATORIES LTD.

  •  

    Semantic Segmentation Based on Multi Dilated Convolution Blocks

    Takayoshi Yamashita, Lecturer, Chubu University

  •  

    Perceiving and Reasoning About Liquids with a Robot

    Connor Schenck, PhD Student, University of Washington Department of Computer Science & Engineering

  •  

    Does Fine-Tuning Fit for Lifelong Machine Learning?

    Takeharu Eda, Manager, NTT

  •  

    Intelligent Systems and Knowledge Discovery for Communication of Extreme Weather and Disaster Preparedness

    Ibrahim Demir, Assistant Professor, University of Iowa

  •  

    Novel Distribution of Memory Intensive Deep Learning Layers for Parallel Multi-GPU Computing

    Ahmed Al-Jarro, Principal Researcher, Fujitsu Laboratories of Europe Ltd.

  •  

    Precipitation Nowcasting: Convolutional Recurrent Neural Networks on Cray Hardware with NVIDIA GPUs

    Jericho E. Cain, Software Engineer, Cray, Inc.

  •  

    Dirty Pixels: Optimizing Image Classification Architectures for Raw Sensor Data

    Felix Heide, Researcher, Stanford University

  •  

    MinPy: JIT(NumPy + Autograd) => MXNet

    Minjie Wang, Student, NYU

  •  

    Efficient Networks for Real Time Operation in Embedded Platforms

    Jose Alvarez, Researcher, CSIRO

  •  

    Tofu: Parallelizing Deep Learning Systems with Automatic Tiling

    Chien-Chin Huang, Student, NYU

  •  

    Combining Tensor Decompositions and Deep Learning for Human Activity Classification

    Vinay Prabhu, Principal Machine Learning Scientist, UnifyID Inc

 
 

CONNECT WITH US

Presented by NVIDIA, GTC is comprised of the annual conference, year-long webinar series, and workshops that connect the global community of developers, researchers, and scientists through unique educational and networking opportunities.