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Driver drowsiness detection using image processing and machine learning

By:

Fahad Rafiq (3169)

Material type: Text

TextPublication details: Islamabad (Unpublished) 2022Description: xii, 34 p. : ill., Col. ; 30 cm. +CDSubject(s):

Electrical Engineering -- Eye aspect ratio feature -- Image frames extraction -- Public circularity feature -- FEAS

DDC classification:

621.3 FAH

Dissertation note: Thesis (M.S.)--Riphah International University, 2022

List(s) this item appears in: FEAS & DBS Thesis I-14 Campus

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Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Thesis	Main Campus	621.3 FAH (Browse shelf(Opens below))	1	NOT for LOAN		69603

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Submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering to the Faculty of Engineering and Applied Sciences

Includes bibliographical references.

Thesis supervisor: Dr. Faraz Akram

Thesis (M.S.)--Riphah International University, 2022

English

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