Paper Info
Title
Performance of Some Image Processing Algorithms in Tensorflow
Abstract
Signal, image and Synthetic Aperture Radar imagery algorithms in recent time are used in a daily routine. Due to huge data and complexity, their processing is almost impossible in a real time. Often image processing algorithms are inherently parallel in nature, so they fit nicely into parallel architectures multicore Central Processing Unit (CPU) and Graphics Processing Unit GPUs. In this paper image processing algorithms were evaluated, which are capable to execute in parallel manner on several platforms CPU and GPU. All algorithms were tested in TensorFlow, which is a novel framework for deep learning, but also for image processing. Relative speedups compared to CPU were given for all algorithms. TensorFlow GPU implementation can outperform multi-core CPUs for tested algorithms, obtained speedups range from 3.6 to 15 times.
Year
DOI
Venue
2018
10.1109/IWSSIP.2018.8439714
2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP)
Keywords
Field
DocType
image processing,tensorflow,parallel processing,central processing unit,graphics processing unit
Synthetic aperture radar imagery,Computer vision,Central processing unit,Computer science,Parallel processing,Image processing,Computational science,Artificial intelligence,Deep learning,Digital image processing,Graphics processing unit,Multi-core processor
Conference
ISSN
ISBN
Citations 
2157-8672
978-1-5386-6980-8
0
PageRank 
References 
Authors
0.34
3
3
Name
Order
Citations
PageRank
Damir Demirovic193.60
Emir Skejic201.35
Amira Serifovic-Trbalic3114.42