has been cited by the following article(s):
|
[1]
|
NGCF-RVFL: Next Generation Convolutional Feature with Random Vector Functional Link for multi-grade diabetic retinopathy detection
Computers and Electrical Engineering,
2026
DOI:10.1016/j.compeleceng.2026.110972
|
|
|
|
|
[2]
|
Graph-Aware Multimodal Deep Learning for Classification of Diabetic Retinopathy Images
IEEE Access,
2025
DOI:10.1109/ACCESS.2025.3564529
|
|
|
|
|
[3]
|
Develop an Ensemble Transfer Learning with Vision Transformers Large Model for Diabetic Retinopathy detection at an earlier stage
2025 7th International Conference on Signal Processing, Computing and Control (ISPCC),
2025
DOI:10.1109/ISPCC66872.2025.11039408
|
|
|
|
|
[4]
|
Enhanced Classification of Diabetic Retinopathy Using Deep Learning Models
2025 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA),
2025
DOI:10.1109/ACCTHPA65749.2025.11168705
|
|
|
|
|
[5]
|
Enhancing Diabetic Retinopathy Classification Using Hybrid Deep and Handcrafted Feature Extraction with Optimized Classifiers
2025 International Conference on Information, Implementation, and Innovation in Technology (I2ITCON),
2025
DOI:10.1109/I2ITCON65200.2025.11210739
|
|
|
|
|
[6]
|
Lesion-Based Diabetic Retinopathy Detection Using Hybrid Deep Learning Models
2025 International Conference on Next Generation of Green Information and Emerging Technologies (GIET),
2025
DOI:10.1109/GIET65294.2025.11234878
|
|
|
|
|
[7]
|
Scalable and Efficient Deep Learning for Diabetic Retinopathy Classification on ARM
2025 IEEE/SBC 37th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD),
2025
DOI:10.1109/SBAC-PAD66369.2025.00036
|
|
|
|