Severity Grading and Early Retinopathy Lesion Detection through Hybrid Inception-ResNet Architecture
- DOI
- 10.3390/s21206933
- Published
- 2021-10-19
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s21206933,
title = {Severity Grading and Early Retinopathy Lesion Detection through Hybrid Inception-ResNet Architecture},
author = {Sana Yasin and Nasrullah Iqbal and Tariq Ali and Umar Draz and Ali Alqahtani and Muhammad Irfan and Abdul Rehman and Adam Glowacz and Samar Alqhtani and Klaudia Proniewska and Frantisek Brumercik and Lukasz Wzorek},
year = {2021},
journal = {Sensors},
doi = {10.3390/s21206933},
url = {https://doi.org/10.3390/s21206933}
}RIS
TY - JOUR TI - Severity Grading and Early Retinopathy Lesion Detection through Hybrid Inception-ResNet Architecture AU - Sana Yasin AU - Nasrullah Iqbal AU - Tariq Ali AU - Umar Draz AU - Ali Alqahtani AU - Muhammad Irfan AU - Abdul Rehman AU - Adam Glowacz AU - Samar Alqhtani AU - Klaudia Proniewska AU - Frantisek Brumercik AU - Lukasz Wzorek PY - 2021 JO - Sensors DO - 10.3390/s21206933 UR - https://doi.org/10.3390/s21206933 ER -
APA
Yasin, S., Iqbal, N., Ali, T., Draz, U., Alqahtani, A., Irfan, M., Rehman, A., Glowacz, A., Alqhtani, S., Proniewska, K., Brumercik, F., & Wzorek, L. (2021). Severity Grading and Early Retinopathy Lesion Detection through Hybrid Inception-ResNet Architecture. Sensors. https://doi.org/10.3390/s21206933
Source records
- crossref · retrieved 2026-09-25T00:34:14.795Z