ВКР Создание IT-стартапа «Scanface» по психодиагностике на основе машинного обучения и стратегии спин-офф проекта «Luna» (на англ.яз.)

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CONTENTS

1. TECHNOLOGY . .. 5

1.1. Description of the underlying technology . . 5

1.2. Genetic prerequisites for technology ... 5

1.3. Features of the perception of human faces ..... 8

1.4. Development of the architecture of the software prototype for

psychodiagnostics and preparation of recommendations .. 10

1.5. Development of modules for determining facial points and face segmentation

for a prototype software for psychodiagnostics and preparation of

recommendations. . 13

1.6. Development of tools for marking datasets for a prototype software for

psychodiagnostics and preparation of recommendations. .. 17

1.7. Development of a database of signs for a prototype software for

psychodiagnostics and preparation of recommendations. ....................................... 18

1.8. Development of an algorithm for identifying features for a prototype software

for psychodiagnostics and preparation of recommendations. ................................. 19

1.9. Assembling a prototype software for psychodiagnostics and preparation of

recommendations. Development of a web service for input and output of data to a

client. 26

1.10. Testing of software prototype and web service for psychodiagnostics and

preparation of recommendations. ............................................................................ 29

1.11. Refinement of the prototype software for psychodiagnostics and preparation

of recommendations based on testing results. ......................................................... 30

1.12. Conclusion .31

2. STRATEGY .34

2.1. Description of the customer problem ............................................................... 34

2.2. Description of an innovative solution to a customer problem .......................... 37

2.3. Markets size ..40

2.4. Target audience ................................................................................................. 42

2.5. Trends used by the product ............................................................................... 46

2.6. Competitors ....................................................................................................... 50

2.7. The users requirements .................................................................................... 52

2.8. Product description ........................................................................................... 54

2.9. Traction ............................................................................................................. 56

2.10. Risks and risk prevention ................................................................................ 59

2.11. Fullskills Team ............................................................................................... 62

2.12. Financial plan .................................................................................................. 70

2.13. Customer acquisition plan .............................................................................. 72

3. PRODUCT DEVELOPMENT 80

3.1. Purpose of the mobile application . 80

3.2. Mobile app functions 80

3.3. Application Components 81

3.4. Requirements for iOS application for image upload and report output ........... 81

3.5. Stages of userflow of the application .. 82

3.6. Stages of the programmers work .. 116

CONCLUSION .. 117

LIST OF REFERENCES ..119

APPENDIX . 122

Appendix No. 1. Description of facial points and facial segments . 122

Appendix No. 2. The process of creating a tool for marking up datasets ............. 128

Appendix No. 3. Psychotypes Table .. 135

Appendix No. 4. Comparison of metrics of testing models .. 140

Appendix No. 5. Financial projection based on cohort analysis…143

Appendix No. 6. Userflow of a mobile application..151

Appendix No. 7. Userflow of a mobile application..152

INTRODUCTION

ScanFace is a unique AI-powered technology that profiles users based on their

facial characteristics by the photo and automatic recommendations that uses machine

learning and computer vision algorithms.