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SiftCU: An Accelerated Cuda Based Implementation of SIFT

Mahdi S. Mohammadi, Mehdi Rezaeian

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GT 440 GT, nVidia GeForce GTX 670, Package

December 2, 2014 by hgpu

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high performance computing on graphics processing units: hgpu.org

SiftCU: An Accelerated Cuda Based Implementation of SIFT

Recent source codes

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

OpenAdSCL

Rgtsvm: Support Vector Machines on a GPU in R

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

gloo: Collective communications library with various primitives for multi-machine training

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

CELES: CUDA-accelerated electromagnetic scattering by large ensembles of spheres

Boda: A C++ Framework for Efficient Experiments in Computer Vision [WIP]

Parallel and in-process compilation of individuals for genetic programming on GPU

ESPRESO: Highly Parallel Solvers for Engineering Applications

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Featured events

4th International Conference on Biomedical and Bioinformatics Engineering (ICBBE), 2017

9th International Conference on Signal Processing Systems (ICSPS), 2017

The 5th International conference on Control, Mechatronics and Automation (ICCMA), 2017

8th International Conference on Biology, Environment and Chemistry (ICBEC), 2017

2nd International Conference on Communication and Information Systems (ICCIS), 2017