1 INTRODUCTION

2 DEEP LEARNING-BASED IRIS SEGMENTATION

3 DEEP LEARNING-BASED IRIS RECOGNITION

4 DEEP LEARNING-BASED IRIS PRESENTATION ATTACK DETECTION

5 DEEP LEARNING-BASED FORENSIC IRIS RECOGNITION

6 HUMAN-MACHINE PAIRING TO IMPROVE DEEP LEARNING-BASED IRIS RECOGNITION

7 RECOGNITION IN LESS CONTROLLED ENVIRONMENTS: IRIS/PERIOCULAR ANALYSIS

8 OPEN-SOURCE DEEP LEARNING-BASED IRIS RECOGNITION TOOLS

9 EMERGING RESEARCH DIRECTIONS

10 CONCLUSIONS