AI and Deep Learning Conference Posters

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

Adversarial Exploration Strategy for Self-Supervised Imitation Learning
Adversarial Exploration Strategy for Self-Supervised Imitation Learning

Chun-Yi Lee, Assistant Professor, Department of Computer Science, National Tsing Hua University

Deep Mesh-Net - A network of deep-learning architectures for medical image analytics
Deep Mesh-Net - A network of deep-learning architectures for medical image analytics

Girish Srinivasan, CTO, DDH

Generating Albums with SampleRNN to Imitate Metal, Rock, and Punk Bands
Generating Albums with SampleRNN to Imitate Metal, Rock, and Punk Bands

CJ Carr,  CTO, Dadabots

Knowledge Distillation with Feature Maps for Image Classification
Knowledge Distillation with Feature Maps for Image Classification

Che-Rung Lee, Professor, National Tsing Hua University

SPIGAN: Privileged Adversarial Learning from Simulation
SPIGAN: Privileged Adversarial Learning from Simulation

Kuan-Hui Lee, Research Scientist, Toyota Research Institute

Toward Effective Data Augmentation with Multi-Domain Learning GANs
Toward Effective Data Augmentation with Multi-Domain Learning GANs

Shin'ya Yamaguchi, Researcher, NTT

Detect-and-Avoid Technology with NVIDIA DrivePX2
Detect-and-Avoid Technology with NVIDIA DrivePX2

Jaehyun Lee, Ph.D. Candidate, KAIST

Multiple RF Signal Detection with Deep Learning Algorithms in Severe Communication Environments
Multiple RF Signal Detection with Deep Learning Algorithms in Severe Communication Environments

Myung-Sun Baek, Senior Researcher, ETRI

Optimized Geometry Design with High Performance Aerodynamic using Deep Learning
Optimized Geometry Design with High Performance Aerodynamic using Deep Learning

Nilton Guedes, Technical Director, Arteonic

Scalable Distributed Deep Learning Inference on Multi-GPU with Hadoop-Spark
Scalable Distributed Deep Learning Inference on Multi-GPU with Hadoop-Spark

Hunmin Yang, Researcher, Agency for Defense Development

Surpassing State-of-the-Art VQA with Deep Learning Optimization Techniques under Limited GPU Resources
Surpassing State-of-the-Art VQA with Deep Learning Optimization Techniques under Limited GPU Resources

Quang Tran, Head of AI, AIOZ Pte Ltd

Attention Branch Network: Learning Attention Mechanism for Visual Explanation
Attention Branch Network: Learning Attention Mechanism for Visual Explanation

Hiroshi Fukui, Ph.D. Student, Chubu University

Basketball Defensive Strategies Generation by Generative Adversarial Network
Basketball Defensive Strategies Generation by Generative Adversarial Network

Jay Chen, Solution Architect, NVIDIA

Chronic Kidney Disease Survival Prediction by Using Artificial Neural Networks
Chronic Kidney Disease Survival Prediction by Using Artificial Neural Networks

Che-Lun Hung, Professor,  Chang Gung University, Taiwan

CLUSE: Cross-Lingual Unsupervised Sense Embedding
CLUSE: Cross-Lingual Unsupervised Sense Embedding

Ta-Chung Chi, Graduate Student, National Taiwan University

CNN Preprocessing for Increased Medical Segmentation Accuracy
CNN Preprocessing for Increased Medical Segmentation Accuracy

Jack Teitel, Sr. Data Scientist, University of Rochester Health lab

Deep Learning Approach for Rain Type Classifications from Microwave Satellite Observations
Deep Learning Approach for Rain Type Classifications from Microwave Satellite Observations

Yeji Choi, Research Associate (Post-Doc), Korea Institute of Science and Technology Information (KISTI)

Deep Reinforcement Learning Routing for Vehicular Ad-Hoc Network
Deep Reinforcement Learning Routing for Vehicular Ad-Hoc Network

Nick Tai, Solution Architect, NVIDIA

DeepDIVA A Highly-Functional Python Framework for Reproducible Experiments
DeepDIVA A Highly-Functional Python Framework for Reproducible Experiments

Marcus Liwicki, Prof. Dr., Lulea University of Technology

DeepSim-HiPAC: Deep Learning-based Platform Converts Physics-based Simulators into Real-time AI Simulators
DeepSim-HiPAC: Deep Learning-based Platform Converts Physics-based Simulators into Real-time AI Simulators

Ahmed Al-Jarro, Principal Researcher, Fujitsu Labs of Europe

Facial Expression Recognition For Detecting Stress using Deep Learning Approach
Facial Expression Recognition For Detecting Stress using Deep Learning Approach

Wonju Seo, Ph.D Candidate, Pohang University of Science and Technology (POSTECH)

Feature Learning Intertwiners
Feature Learning Intertwiners

Hongyang Li, Ph.D Student, The Chinese Univ. of HK

Impact of Demographic Imbalance in Deep Face Recognition
Impact of Demographic Imbalance in Deep Face Recognition

Carles Fernandez, Director of Research, Herta Security

Multi Task and Multi modal Conditional Imitation Learning for Autonomous driving
Multi Task and Multi modal Conditional Imitation Learning for Autonomous driving

Adithya Pravarun Reddy Ranga, Software Engineering - Machine Learning Research, Valeo North America Inc.

NU-EA-Net: On-device Convolutional Neural Networks Model using Evolutionary Algorithm
NU-EA-Net: On-device Convolutional Neural Networks Model using Evolutionary Algorithm

Chakkrit Termritthikun, Ph.D Student, Naresuan University

Real-Time Freespace Segmentation on Autonomous Robots for Detection of Obstacles and Drop-Offs
Real-Time Freespace Segmentation on Autonomous Robots for Detection of Obstacles and Drop-Offs

Anish Singhani, Deep Learning Researcher, Independent

Transfer Learning on 18F-FDG PET for Predicting Treatment Failure of Cancer Patients
Transfer Learning on 18F-FDG PET for Predicting Treatment Failure of Cancer Patients

Wei-Chih Shen, Associate Professor, Asia University

TrIMS: Transparent and Isolated Model Sharing for LowLatency Deep Learning Inference in Function as a Service
TrIMS: Transparent and Isolated Model Sharing for LowLatency Deep Learning Inference in Function as a Service

Jinjun Xiong, Student, IBM Thomas J Watson Research Center

Unsupervised Feature Learning by Hierarchical Competitive Learning in Convolutional Neural Networks
Unsupervised Feature Learning by Hierarchical Competitive Learning in Convolutional Neural Networks

Takashi Shinozaki, Researcher, National Institute of Information and Communications Technology

Using Belief Networks to Evaluate the Quality of an Expert
Using Belief Networks to Evaluate the Quality of an Expert

Maria Pantoja,Assistant Professor, CalPoly SLO

Volumetric Prostate Segmentation from MR Images using Fully Convolutional Neural Network
Volumetric Prostate Segmentation from MR Images using Fully Convolutional Neural Network

Aman Agarwal, Student, Nirma University

VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions
VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions

Qingyi Tao, Solutions Architect, NVIDIA

Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning
Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning

Aishwarya Agrawal, Ph.D Candidate, Georgia Institute of Technology  

GPU-Accelerated Overlapping Speech Transcription
GPU-Accelerated Overlapping Speech Transcription

Blake Holman, AI Development Engineer, Advantest

Medical Record Machine Reading via Deep Attention Networks
Medical Record Machine Reading via Deep Attention Networks

Jay Urbain, Professor, Milwaukee School of Engineering

DeepJet: A Machine Learning Environment for High-energy Physics
DeepJet: A Machine Learning Environment for High-energy Physics

Swapneel Mehta, Technical Student, European Organisation for Nuclear Research (CERN)

Dermatopathology Diagnostics with GPU-accelerated Deep Learning Algorithms
Dermatopathology Diagnostics with GPU-accelerated Deep Learning Algorithms

Rajath Soans, Senior Research Scientist, Proscia Inc

Exploiting CUDA Unified Memory for Efficient Out-of-Core DNN Training
Exploiting CUDA Unified Memory for Efficient Out-of-Core DNN Training

Ammar Ahmad Awan, Graduate Student, The Ohio State University

Fast Data Pre-processing with DALI
Fast Data Pre-processing with DALI

Janusz Lisiecki, Deep Learning Manager, NVIDIA

Fast deep learning library implemented in C++
Fast deep learning library implemented in C++

Yuki Shindo, Software Engineer, Computermind corp.

MLModelScope: Evaluate and Measure Machine Learning Models Consistently
MLModelScope: Evaluate and Measure Machine Learning Models Consistently

Cheng Li, Student, University of Illinois at Urbana-Champaign

Novel Hierarchical All-Reduce on Multi-tired Network for Deep Learning
Novel Hierarchical All-Reduce on Multi-tired Network for Deep Learning

Minsik cho, Research Staff Member, IBM Research

Spatial Parallel Convolution for Scalable Training of Large Neural Networks
Spatial Parallel Convolution for Scalable Training of Large Neural Networks

Naoya Maruyama, Computer Scientist, Lawrence Livermore National Laboratory

Triton: A Language and Super-Optimizing Compiler for Deep Learning
Triton: A Language and Super-Optimizing Compiler for Deep Learning

Philippe Tillet, Ph.D. Candidate, Harvard University

μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batches
μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batches

Yosuke Oyama, Student, Tokyo Institute of Technology

Adversarial Exploration Strategy for Self-Supervised Imitation Learning
Deep Mesh-Net - A network of deep-learning architectures for medical image analytics
Generating Albums with SampleRNN to Imitate Metal, Rock, and Punk Bands
Knowledge Distillation with Feature Maps for Image Classification
SPIGAN: Privileged Adversarial Learning from Simulation
Toward Effective Data Augmentation with Multi-Domain Learning GANs
Detect-and-Avoid Technology with NVIDIA DrivePX2
Multiple RF Signal Detection with Deep Learning Algorithms in Severe Communication Environments
Optimized Geometry Design with High Performance Aerodynamic using Deep Learning
Scalable Distributed Deep Learning Inference on Multi-GPU with Hadoop-Spark
Surpassing State-of-the-Art VQA with Deep Learning Optimization Techniques under Limited GPU Resources
Attention Branch Network: Learning Attention Mechanism for Visual Explanation
Basketball Defensive Strategies Generation by Generative Adversarial Network
Chronic Kidney Disease Survival Prediction by Using Artificial Neural Networks
CLUSE: Cross-Lingual Unsupervised Sense Embedding
CNN Preprocessing for Increased Medical Segmentation Accuracy
Deep Learning Approach for Rain Type Classifications from Microwave Satellite Observations
Deep Reinforcement Learning Routing for Vehicular Ad-Hoc Network
DeepDIVA A Highly-Functional Python Framework for Reproducible Experiments
DeepSim-HiPAC: Deep Learning-based Platform Converts Physics-based Simulators into Real-time AI Simulators
Facial Expression Recognition For Detecting Stress using Deep Learning Approach
Feature Learning Intertwiners
Impact of Demographic Imbalance in Deep Face Recognition
Multi Task and Multi modal Conditional Imitation Learning for Autonomous driving
NU-EA-Net: On-device Convolutional Neural Networks Model using Evolutionary Algorithm
Real-Time Freespace Segmentation on Autonomous Robots for Detection of Obstacles and Drop-Offs
Transfer Learning on 18F-FDG PET for Predicting Treatment Failure of Cancer Patients
TrIMS: Transparent and Isolated Model Sharing for LowLatency Deep Learning Inference in Function as a Service
Unsupervised Feature Learning by Hierarchical Competitive Learning in Convolutional Neural Networks
Using Belief Networks to Evaluate the Quality of an Expert
Volumetric Prostate Segmentation from MR Images using Fully Convolutional Neural Network
VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions
Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning
GPU-Accelerated Overlapping Speech Transcription
Medical Record Machine Reading via Deep Attention Networks
DeepJet: A Machine Learning Environment for High-energy Physics
Dermatopathology Diagnostics with GPU-accelerated Deep Learning Algorithms
Exploiting CUDA Unified Memory for Efficient Out-of-Core DNN Training
Fast Data Pre-processing with DALI
Fast deep learning library implemented in C++
MLModelScope: Evaluate and Measure Machine Learning Models Consistently
Novel Hierarchical All-Reduce on Multi-tired Network for Deep Learning
Spatial Parallel Convolution for Scalable Training of Large Neural Networks
Triton: A Language and Super-Optimizing Compiler for Deep Learning
μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batches
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