Recently, deep convolutional neural network (CNN) has achieved great success for image restoration (IR) and provided hierarchical features at the same time. However, most CNN based IR models do not make full use of from original low-quality images; thereby, resulting in relatively-low performance. In this work, we propose a novel efficient residual dense (RDN) to address problem IR, by making b...

It is very difficult and expensive to replace sensor node battery in wireless sensor network in many critical conditions such as bridge supervising, resource exploration in hostile locations, and wildlife safety, etc. The natural choice in such situations is to maximize network lifetime. One such approach is to divide the sensing area of wireless sensor network into clusters to achieve high ene...

With the increasing integration of neural networks as components in mission-critical systems, there is an need to ensure that they satisfy various safety and liveness requirements. In recent years, numerous sound complete verification methods have been proposed towards end, but these typically suffer from severe scalability limitations. Recent work has enhancing such techniques with abstraction...

The wireless sensor network (WSN) is typically comprised many tiny nodes equipped with processors, sender/receiver antenna and limited battery in which it is impossible or not economic to recharge. Meanwhile, network lifespan is one of the most critical issues because of limited and not renewal used battery in WSN. Several mechanisms have been proposed to prolong network lifespan such as LEACH,...

The wireless sensor network (WSN) is typically comprised many tiny nodes equipped with processors, sender/receiver antenna and limited battery in which it is impossible or not economic to recharge. Meanwhile, network lifespan is one of the most critical issues because of limited and not renewal used battery in WSN. Several mechanisms have been proposed to prolong network lifespan such as LEACH,...

In this article, we take one step toward understanding the learning behavior of deep residual networks, and supporting the hypothesis that deep residual networks are exponential ensembles by construction. We examine the effective range of ensembles by introducing multi-residual networks that significantly improve classification accuracy of residual networks. The multi-residual networks increase...

an efficient cluster head selection algorithm in wireless sensor networks is proposed in this paper. the implementation of the proposed algorithm can improve energy which allows the structured representation of a network topology. according to the residual energy, number of the neighbors, and the centrality of each node, the algorithm uses fuzzy inference systems to select cluster head. the alg...

............................................................................................................................ii APPENDED PAPERS.................................................................................................................iii DIVISION OF WORK BETWEEN AUTHORS.................................................................................iv TABLE OF CONTENTS........