The main purpose of this work is to propose a robust approach for dangerous sound events detection (e.g. gunshots) improve recent surveillance systems. Despite the fact that and classification different has long history in signal processing, analysis environmental sounds still challenging. most works aim prefer time-frequency 2-D representation as input feed convolutional neural networks. This ...

A very deep convolutional neural network (CNN) has recently achieved great success for image super-resolution (SR) and offered hierarchical features as well. However, most deep CNN based SR models do not make full use of the hierarchical features from the original low-resolution (LR) images, thereby achieving relatively-low performance. In this paper, we propose a novel residual dense network (...

sensor networks generally consist of a very great number of sensor nodes which will be spread into a vast environment and aggregate data out of it. the sensor nodes are afflicted with some limitations as follows memory, reception, communication as well as calculation capability, and battery power. the transmission of a great amount of extra data increases data transmission and proportionally in...

A sensor network is made up of a large number of sensors with limited energy. Sensors collect environmental data then send them to the sink. Energy efficiency and thereby increasing the lifetime of sensor networks is important. Direct transfer of the data from each node to the central station will increase energy consumption. Previous research has shown that the organization of nodes in cluster...

Abstract Facial expressions are an important part of human emotional signals and their recognition has become topic research in the field pattern recognition. Deep learning based methods have achieved great success facial expressions. However, with evolution convolution neural networks increased network depth, these suffer from problems such as degraded performance loss feature information. To ...

Abstract Video target tracking is one of hot fields computer vision, and its application also very extensive. However, due to the complexity variability environment, which brings some challenges research tracking. ECO(Efficient Convolution Operators) Algorithm proposed based on convolutional neural network in three aspects. Firstly, residual ResNet50 adopted instead extract appearance features ...