Driver drowsiness detection using image processing and machine learning
Fahad Rafiq (3169)
Driver drowsiness detection using image processing and machine learning - Islamabad (Unpublished) 2022 - xii, 34 p. : ill., Col. ; 30 cm. +CD
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
Electrical Engineering--Eye aspect ratio feature--Image frames extraction--Public circularity feature--FEAS
621.3 / FAH
Driver drowsiness detection using image processing and machine learning - Islamabad (Unpublished) 2022 - xii, 34 p. : ill., Col. ; 30 cm. +CD
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
Electrical Engineering--Eye aspect ratio feature--Image frames extraction--Public circularity feature--FEAS
621.3 / FAH