Ensemble learning combines several individual models to obtain better generalization
performance. Currently, deep learning architectures are showing better performance …

Diabetic retinopathy (DR) results in vision loss if not treated early. A computer-aided
diagnosis (CAD) system based on retinal fundus images is an efficient and effective method …

Automatic screening of diabetic retinopathy (DR) is a well-identified area of research in the
domain of computer vision. It is challenging due to structural complexity and a marginal …

Retinal image analysis holds an imperative position for the identification and classification of
retinal diseases such as Diabetic Retinopathy (DR), Age Related Macular Degeneration …

In contrast to conventional optical imaging modalities, hyperspectral imaging (HSI) is able to
capture much more information from a certain scene, both within and beyond the visual …

Deep learning (DL) enables the creation of computational models comprising multiple
processing layers that learn data representations at multiple levels of abstraction. In the …

Automated retinal vessel segmentation is among the most significant application and
research topics in ophthalmologic image analysis. Deep learning based retinal vessel …

Automatic segmentation of retinal blood vessels from fundus images plays an important role
in the computer aided diagnosis of retinal diseases. The task of blood vessel segmentation …

Circular ribonucleic acids (circRNAs) are widely expressed in cells and tissues and play vital
roles in cellular physiological processes. Their expressions are associated with …

The medical field is creating large amount of data that physicians are unable to decipher
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …