Name
Abstract | ||
|---|---|---|
In developing countries around the world, a multitude of infants continue to suffer and die from vaccine-preventable diseases, and malnutrition. Lamentably, the lack of any official identification documentation makes it exceedingly difficult to prevent these infant deaths. To solve this global crisis, we propose Infant-Prints which is comprised of (i) a custom, compact, low-cost (85 USD), high-resolution (1,900 ppi) fingerprint reader, (ii) a high-resolution fingerprint matcher, and (iii) a mobile application for search and verification for the infant fingerprint. Using Infant-Prints, we have collected a longitudinal database of infant fingerprints and demonstrate its ability to perform accurate and reliable recognition of infants enrolled at the ages 0-3 months, in time for effective delivery of critical vaccinations and nutritional supplements (TAR=90% @ FAR = 0.1% for infants older than 8 weeks). |
Year | Venue | Field |
|---|---|---|
2019 | arXiv: Computer Vision and Pattern Recognition | Fingerprint recognition,Computer science,Developing country,Fingerprint,Malnutrition,Artificial intelligence,Medical emergency,Documentation,Machine learning,Infant mortality |
DocType | Volume | Citations |
Journal | abs/1904.01091 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joshua J. Engelsma | 1 | 22 | 5.78 |
| Debayan Deb | 2 | 64 | 7.25 |
| Anil K. Jain | 3 | 870 | 220.50 |
| Prem Sewak Sudhish | 4 | 10 | 2.69 |
| Anjoo Bhatnager | 5 | 0 | 0.34 |