Deep neural networks have enhanced the performance of decision making systems in many applications, including image understanding, and further gains can be achieved by constructing ensembles. However, designing an ensemble deep is often not very beneficial since time needed to train generally high or gain obtained significant. In this paper, we analyse error correcting output coding (ECOC) fram...

In human eye, the state of blood vessel is a crucial diagnostic factor. The segmentation from fundus image difficult due to spatial complexity, adjacency, overlapping and variability vessel. detection ophthalmic pathologies like hypertensive disorders, diabetic retinopathy cardiovascular diseases are remain challenging task wide-ranging distribution vessels. this paper, Stacked Autoencoder CNN ...

Different eye disease has clinical use in defining of the actual status eye, outcome medication and other alternatives curative phase. Mainly simplicity, nature are most important requirements for any classification system. In existing they used different machine learning techniques to detect only single disease. Whereas deep system, which is named as Convolutional neural networks (CNNs) can sh...