Publication result detail

COMPUTING PLATFORMS FOR DEEP LEARNING TASK IN COMPUTER VISION

KRATOCHVÍLA, L.

Original Title

COMPUTING PLATFORMS FOR DEEP LEARNING TASK IN COMPUTER VISION

English Title

COMPUTING PLATFORMS FOR DEEP LEARNING TASK IN COMPUTER VISION

Type

Paper in proceedings (conference paper)

Original Abstract

The recent progress in machine learning in computer vision guides to enormous hardware requirements. This paper discovers new innovative hardware capable to deal with immense demands.The main concern is on five domains: single-board computers, hardware accelerators, graphics cards, workstations, and cloud computing. These devices have several key features for detection that are discussed. Cloud computing is another presented approach. Different delivery models of cloud computing are addressed.

English abstract

The recent progress in machine learning in computer vision guides to enormous hardware requirements. This paper discovers new innovative hardware capable to deal with immense demands.The main concern is on five domains: single-board computers, hardware accelerators, graphics cards, workstations, and cloud computing. These devices have several key features for detection that are discussed. Cloud computing is another presented approach. Different delivery models of cloud computing are addressed.

Keywords

Deep learning; Hardware; Cloud computing

Key words in English

Deep learning; Hardware; Cloud computing

Authors

KRATOCHVÍLA, L.

RIV year

2021

Released

23.04.2020

Publisher

Vysoké učené Technické, Fakulta elektrotechniky a komunikačních technologií

Location

Brno

ISBN

978-80-214-5868-0

Book

Proceedings II of the 26th Conference STUDENT EEICT 2020

Pages from

171

Pages to

175

Pages count

5

BibTex

@inproceedings{BUT164115,
  author="Lukáš {Kratochvíla}",
  title="COMPUTING PLATFORMS FOR DEEP LEARNING TASK IN COMPUTER VISION",
  booktitle="Proceedings II of the 26th Conference STUDENT EEICT 2020",
  year="2020",
  pages="171--175",
  publisher="Vysoké učené Technické, Fakulta elektrotechniky a komunikačních technologií",
  address="Brno",
  isbn="978-80-214-5868-0"
}

Documents

EEICT2020_final