Name
Abstract | ||
|---|---|---|
Conjunctivitis is a common ocular disease characterized by infection or swelling in the outer membrane of human eye. This contagious ocular disease could be controlled and well treated by medicines depending upon it's category. To realize the connection between Conjunctivitis and other viral diseases, even for COVID-19, timely detection plays an important role. In this study, we have designed a mobile healthcare application (iConDet) through which initial level of Conjunctivitis detection is possible. Deep learning techniques have been used upon the Conjunctivitis dataset prepared by us in support of the claim and to achieve the desired accuracy of 84%. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/978-3-030-82269-9_3 | APPLIED INTELLIGENCE AND INFORMATICS, AII 2021 |
Keywords | DocType | Volume |
Conjunctivitis, Mobile application, Deep learning, Transfer learning, Machine learning | Conference | 1435 |
ISSN | Citations | PageRank |
1865-0929 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Prateeti Mukherjee | 1 | 0 | 0.68 |
| Ishita Bhattacharyya | 2 | 0 | 0.34 |
| Meghma Mullick | 3 | 0 | 0.34 |
| Rahul Kumar | 4 | 289 | 33.86 |
| Nilanjana Dutta Roy | 5 | 0 | 0.34 |
| Mufti Mahmud | 6 | 0 | 2.37 |