high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science » Computer vision

GPU-accelerated real-time stixel computation

Daniel Hernandez-Juarez, Antonio Espinosa, David Vazquez, Antonio Manuel Lopez, Juan Carlos Moure

View

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Package

October 15, 2016 by hgpu

Training a Feedback Loop for Hand Pose Estimation

Markus Oberweger, Paul Wohlhart, Vincent Lepetit

View

Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX 780 Ti, Package, Theano

October 4, 2016 by hgpu

The CUDA LATCH Binary Descriptor: Because Sometimes Faster Means Better

Christopher Parker, Matthew Daiter, Kareem Omar, Gil Levi, Tal Hassner

View

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 1080, Package

September 17, 2016 by hgpu

OpenCL-accelerated object classification in video streams using Spatial Pooler of Hierarchical Temporal Memory

Maciej Wielgosz, Marcin Pietron

View

Tags: Algorithms, AMD Radeon R9 390, ATI, Computer science, Computer vision, Machine learning, OpenCL, Package, PyOpenCL, Python

August 8, 2016 by hgpu

FPGA-Based Accelerator Design from a Domain-Specific Language

M. Akif Ozkan, Oliver Reiche, Frank Hannig, Jurgen Teich

View

Tags: Algorithms, Computer vision, FPGA, Heterogeneous systems, Image processing, nVidia, nVidia Jetson TK1, OpenCL, Tesla K20

July 26, 2016 by hgpu

OpenFace: A general-purpose face recognition library with mobile applications

Brandon Amos, Bartosz Ludwiczuk, Mahadev Satyanarayanan

View

Tags: Computer science, Computer vision, CUDA, Deep learning, Lua, Neural networks, nVidia, Package, Python, Tesla K40

July 13, 2016 by hgpu

Comparing Parallel Hardware Architectures for Visually Guided Robot Navigation

Wolfram Schenck, Michael Horst, Tim Tiedemann, Sergius Gaulik, Ralf Moller

View

Tags: ATI, ATI Radeon HD 7970, Computer science, Computer vision, FPGA, nVidia, nVidia GeForce GTX 570, nVidia Quadro NVS 4200 M, OpenCL, Review, Robotics

July 11, 2016 by hgpu

Fast Predictive Image Registration

Xiao Yang, Roland Kwitt, Marc Niethammer

View

Tags: Bayesian, Computer science, Computer vision, CUDA, Deep learning, Image registration, nVidia, nVidia GeForce GTX Titan X, Package, Python

July 11, 2016 by hgpu

A Test Drive of the NVIDIA Jetson TX1 Developer Kit for Deep Learning and Computer Vision Applications

BDTI staff

View

Tags: Algorithms, Caffe, Computer science, Computer vision, CUDA, Deep learning, nVidia, nVidia Jetson TK1, nVidia Tegra TX1, OpenCV

July 5, 2016 by hgpu

DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

Chenghua Li, Qi Kang, Guojing Ge, Qiang Song, Hanqing Lu, Jian Cheng

View

Tags: Computer science, Computer vision, CUDA, Deep learning, Image recognition, Neural networks, nVidia, nVidia GeForce GTX Titan Black, nVidia GeForce GTX Titan X

June 30, 2016 by hgpu

YodaNN: An Ultra-Low Power Convolutional Neural Network Accelerator Based on Binary Weights

Renzo Andri, Lukas Cavigelli, Davide Rossi, Luca Benini

View

Tags: Computer science, Computer vision, Deep learning, Hardware Architecture, Neural networks

June 21, 2016 by hgpu

Weighted Residuals for Very Deep Networks

Falong Shen, Gang Zeng

View

Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X

June 2, 2016 by hgpu

Watershed analysis algorithm implementation in CUDA and OpenACC

Parallelizing Multiple Flow Accumulation Algorithm using CUDA and OpenACC

OpenCL Performance Prediction using Architecture-Independent Features

Characterizing and Predicting Scientific Workloads for Heterogeneous Computing Systems

PySPH: a Python-based SPH framework

PySPH: a Python-based framework for smoothed particle hydrodynamics

Efficient Interleaved Batch Matrix Solvers for CUDA

Efficient Interleaved Batch Matrix Solvers for CUDA

ArborX: Performance-portable geometric search library

ArborX: A Performance Portable Search Library

FlowSeq: Generative Flow based Sequence-to-Sequence Toolkit

FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow

Compositional Deep Learning in Futhark

Compositional Deep Learning in Futhark

MLPerf Benchmark Suite

Demystifying the MLPerf Benchmark Suite

stdgpu: Efficient STL-like Data Structures on the GPU

stdgpu: Efficient STL-like Data Structures on the GPU

ikra-cpp: C++ Library for Object-oriented Programming with Structure of Arrays Layout

Memory-Efficient Object-Oriented Programming on GPUs

See all packages

* * *

* * *

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

+

HGPU group © 2010-2019 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: