Performance comparison of FPGA, GPU and CPU in image processing
By Shuichi Asano, T. Maruyama, Y. Yamaguchi. International Conference on Field-Programmable Logic and Applications, 2009
300 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/d70a2c44b9c22348600b7359ffc43d36876c5a42
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Ishita Das
- Ujjwal Maulik
- Nibaran Das
- Swarnendu Ghosh
- Ganapati Panda
- Satyasai Jagannath Nanda
- Abdolreza Hatamlou
- Ke-Lin Du
Citations in the corpus
- Understanding Deep Learning Techniques for Image Segmentation (2019, methodology): “But with the onset of graphics processing units(GPUs) [7] developed by Nvidia and their underlying CUDA api for accessing the parallel compute cores neural learning systems got a significant boost.”