Detection of sickle cell anemia using image processing and machine learning techniques

By: Material type: TextTextPublication details: Lahore (unpublished) 2022Description: xi, 43 p. : ill. ; 29.3 cm. +CDSubject(s): DDC classification:
  • 006.4 SAJ
Dissertation note: Thesis (MS)--Riphah International University, 2022 Registration no:F20C14G32016
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Item type Current library Call number Status Date due Barcode
Thesis Thesis Lahore Raiwind Campus 006.4 HAF (Browse shelf(Opens below)) Not for loan 59781

Submitted in fulfillment of the requirements for the degree of Master of Science to the Faculty of electrical engineering

Includes bibliographical references

Thesis supervisor: Engr Ishfaq Ahmad

Thesis (MS)--Riphah International University, 2022

Registration no:F20C14G32016

English

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