Deep learning framework for iridology

By: Material type: TextTextPublication details: Islamabad (unpublished) 2017Description: iii, 26 p. : ill . ; 30 cm. +CDSubject(s): DDC classification:
  • 617.71 FAW
Dissertation note: Thesis (MS)--Riphah International Univeristy, 2017
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 Thesis Main Campus 617.71 FAW (Browse shelf(Opens below)) 1 NOT for LOAN 28743

Submitted in fulfillment of the requirements for the degree of Master of Science in Electrical Engineering for the Faculty of Engineering and Applied Science.

Includes bibliographical references.

Thesis Supervisor: Dr Tassadaq Hussain

Thesis (MS)--Riphah International Univeristy, 2017

English

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