Visual Task Classification using Classic Machine Learning and CNNs

Devangi Vilas Chinchankarame; Noha Elfiky; Nada Attar

doi:10.11159/mhci22.110

Visual Task Classification using Classic Machine Learning and CNNs

Devangi Vilas Chinchankarame
, Noha Elfiky
, Nada Attar

Saint Mary's College of California

San Jose State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022
Editors	Luigi Benedicenti, Zheng Liu
Publisher	Avestia Publishing
ISBN (Print)	9781990800092
DOIs	https://doi.org/10.11159/mhci22.110
State	Published - 2022
Event	8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022 - Prague, Czech Republic Duration: Jul 28 2022 → Jul 30 2022

Publication series

Name	Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science
ISSN (Electronic)	2369-811X

Conference

Conference	8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022
Country/Territory	Czech Republic
City	Prague
Period	7/28/22 → 7/30/22

ASJC Scopus Subject Areas

Computer Networks and Communications
Information Systems
Artificial Intelligence
Human-Computer Interaction
Electrical and Electronic Engineering
Biomedical Engineering

Keywords

CNN
Eye Tracking
Machine Learning
Vision
Visual search

Access to Document

10.11159/mhci22.110

Cite this

Chinchankarame, D. V., Elfiky, N., & Attar, N. (2022). Visual Task Classification using Classic Machine Learning and CNNs. In L. Benedicenti, & Z. Liu (Eds.), Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022 Article MHCI 110 (Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science). Avestia Publishing. https://doi.org/10.11159/mhci22.110

Chinchankarame, Devangi Vilas, Noha Elfiky and Nada Attar. "Visual Task Classification using Classic Machine Learning and CNNs." Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022, edited by Luigi Benedicenti and Zheng Liu, Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science., Avestia Publishing, 2022. https://doi.org/10.11159/mhci22.110

Visual Task Classification using Classic Machine Learning and CNNs. / Chinchankarame, Devangi Vilas; Elfiky, Noha; Attar, Nada.
Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022. ed. / Luigi Benedicenti; Zheng Liu. Avestia Publishing, 2022. MHCI 110 (Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chinchankarame, DV, Elfiky, N & Attar, N 2022, Visual Task Classification using Classic Machine Learning and CNNs. in L Benedicenti & Z Liu (eds), Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022., MHCI 110, Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science, Avestia Publishing, 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022, Prague, Czech Republic, 7/28/22. https://doi.org/10.11159/mhci22.110

Chinchankarame DV, Elfiky N, Attar N. Visual Task Classification using Classic Machine Learning and CNNs. In Benedicenti L, Liu Z, editors, Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022. Avestia Publishing. 2022. MHCI 110. (Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science). doi: 10.11159/mhci22.110

Chinchankarame, Devangi Vilas ; Elfiky, Noha ; Attar, Nada. / Visual Task Classification using Classic Machine Learning and CNNs. Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022. editor / Luigi Benedicenti ; Zheng Liu. Avestia Publishing, 2022. (Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science).

@inproceedings{d8dc87cc2552416ba021dc2f63d8aea1,

title = "Visual Task Classification using Classic Machine Learning and CNNs",

keywords = "CNN, Eye Tracking, Machine Learning, Vision, Visual search",

author = "Chinchankarame, \{Devangi Vilas\} and Noha Elfiky and Nada Attar",

note = "Publisher Copyright: {\textcopyright} 2022, Avestia Publishing. All rights reserved.; 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022 ; Conference date: 28-07-2022 Through 30-07-2022",

year = "2022",

doi = "10.11159/mhci22.110",

language = "English",

isbn = "9781990800092",

series = "Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science",

publisher = "Avestia Publishing",

editor = "Luigi Benedicenti and Zheng Liu",

booktitle = "Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022",

}

TY - GEN

T1 - Visual Task Classification using Classic Machine Learning and CNNs

AU - Chinchankarame, Devangi Vilas

AU - Elfiky, Noha

AU - Attar, Nada

PY - 2022

Y1 - 2022

KW - CNN

KW - Eye Tracking

KW - Machine Learning

KW - Vision

KW - Visual search

UR - https://www.scopus.com/pages/publications/85141848432

UR - https://www.scopus.com/pages/publications/85141848432#tab=citedBy

U2 - 10.11159/mhci22.110

DO - 10.11159/mhci22.110

M3 - Conference contribution

AN - SCOPUS:85141848432

SN - 9781990800092

T3 - Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science

BT - Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022

A2 - Benedicenti, Luigi

A2 - Liu, Zheng

PB - Avestia Publishing

T2 - 8th World Congress on Electrical Engineering and Computer Systems and Science, EECSS 2022

Y2 - 28 July 2022 through 30 July 2022

ER -

Visual Task Classification using Classic Machine Learning and CNNs

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Cite this