For a target task where the labeled data are unavailable, domain adaptation can transfer learner from different source domain. Previous deep methods mainly learn global shift, i.e., align and distributions without considering relationships between two subdomains within same category of domains, leading to unsatisfying learning performance capturing fine-grained information. Recently, more resea...

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...

A Deep Neural Sentiment Classification Network (DNSCN) is developed in this work to classify the Twitter data unambiguously. It attempts extract negative and positive sentiments database. The main goal of system find sentiment behavior tweets with minimum ambiguity. well-defined neural network extracts deep features from automatically. Before extracting deeper deeper, text each tweet represente...