Neural networks | Page 37

hgpu.org » Neural networks

Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection

Yi Hou, Hong Zhang, Shilin Zhou

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia Quadro K4200, Pattern recognition, Robotics

April 23, 2015 by hgpu

Caffe con Troll: Shallow Ideas to Speed Up Deep Learning

Firas Abuzaid, Stefan Hadjis, Ce Zhang, Christopher Re

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GRID K520, Tesla K40

April 20, 2015 by hgpu

A Convolutional Neural Network Cascade for Face Detection

Haoxiang Li, Zhe Lin, Xiaohui Shen, Jonathan Brandt, Gang Hua

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Tags: CNN, Computer science, CUDA, Deep learning, Face detection, Neural networks, nVidia, nVidia GeForce GTX Titan

April 20, 2015 by hgpu

Deep convolutional networks for pancreas segmentation in CT imaging

Holger R. Roth, Amal Farag, Le Lu, Evrim B. Turkbey, Ronald M. Summers

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Tags: Computed tomography, CT, CUDA, Deep learning, Medicine, Neural networks, nVidia, nVidia GeForce GTX Titan Z, Tomography

April 17, 2015 by hgpu

Image Classification with Pyramid Representation and Rotated Data Augmentation on Torch 7

Keven (Kedao) Wang

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GRID K520

April 14, 2015 by hgpu

Multi-Lingual Speech Recognition with Low-Rank Multi-Task Deep Neural Networks

Aanchan Mohan, Richard Rose

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Speech recognition, Tesla K20

April 7, 2015 by hgpu

Face Retriever: Pre-filtering the Gallery via Deep Neural Net

Dayong Wang, Anil K. Jain

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, Filtering, Machine learning, Neural networks, nVidia, Tesla K20

March 30, 2015 by hgpu

Single stream parallelization of generalized LSTM-like RNNs on a GPU

Kyuyeon Hwang, Wonyong Sung

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Tags: Algorithms, Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K40

March 22, 2015 by hgpu

Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning

Ken Miura, Tatsuya Harada

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Source codes

Tags: Algorithms, Computer science, Java, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, WebCL

March 20, 2015 by hgpu

Portable GPU-Based Artificial Neural Networks for Accelerated Data-Driven Modeling

Zheng Yi Wu, Mahmoud Elmaghraby

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 460, nVidia Quadro FX 770 M, OpenCL

March 18, 2015 by hgpu

GPGPU Performance and Power Estimation Using Machine Learning

Gene Wu, Joseph L. Greathouse, Alexander Lyashevsky, Nuwan Jayasena, Derek Chiou

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Tags: ATI, ATI Radeon HD 7970, Computer science, Energy-efficient computing, Machine learning, Neural networks, OpenCL

March 12, 2015 by hgpu

Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification

Dashiell Bodington, Eric Greenstein, Matthew Hu

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 780

March 12, 2015 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection

Caffe con Troll: Shallow Ideas to Speed Up Deep Learning

A Convolutional Neural Network Cascade for Face Detection

Deep convolutional networks for pancreas segmentation in CT imaging

Image Classification with Pyramid Representation and Rotated Data Augmentation on Torch 7

Multi-Lingual Speech Recognition with Low-Rank Multi-Task Deep Neural Networks

Face Retriever: Pre-filtering the Gallery via Deep Neural Net

Single stream parallelization of generalized LSTM-like RNNs on a GPU

Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning

Portable GPU-Based Artificial Neural Networks for Accelerated Data-Driven Modeling

GPGPU Performance and Power Estimation Using Machine Learning

Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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