As a new classification platform, deep learning has recently received increasing attention from researchers and has been successfully applied to many domains. In some domains, like bioinformatics and robotics, it is very difficult to construct a large-scale well-annotated dataset due to the expense of data acquisition and costly annotation, which limits its development. Transfer learning relaxes the hypothesis that the training data must be independent and identically distributed (i.i.d.) with the test data, which motivates us to use transfer learning to solve the problem of insufficient training data. This survey focuses on reviewing the current researches of transfer learning by using deep neural network and its applications. We defined deep transfer learning, category and review the recent research works based on the techniques used in deep transfer learning.

No abstract

No abstract

No abstract

The sharing of patients' locations is an important part in mobile medical services and modern smart healthcare. Although location sharing based on blockchains has advantages on decentralization and openness, there is also a challenge to guarantee the security and the privacy of locations recorded in a blockchain. To this end, this paper investigates the location sharing based on blockchains for telecare medical information systems. Firstly, we define the basic requirements of blockchain-based location sharing including decentralization, unforgeability, confidentiality, multi-level privacy protection, retrievability and verifiability. Then, using order-preserving encryption and merkle tree, we propose a blockchain-based multi-level location sharing scheme, i.e. BMPLS. The analysis results show that our scheme satisfies the above requirements. Finally, the performance of our scheme is evaluated and the experiment results show that our scheme is efficient and feasible for both patients and medical workers. In a word, our scheme can be applied to realize privacy-preserving location sharing based on blockchains for telecare medical information systems.

No abstract

No abstract

No abstract