An Embodied Multi-Sensor Fusion Approach to Visual Motion Estimation Using Unsupervised Deep Networks

Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks

The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced using considering the focus measurement in the spatial domain. However, the multi-focus image ...

Visual Marker based Multi-Sensor Fusion State Estimation

This paper presents the description and experimental results of a versatile Visual Marker based Multi-Sensor Fusion State Estimation that allows to combine a variable optional number of sensors and positioning algorithms in a loosely-coupling fashion, incorporating visual markers to increase its performances. This technique allows an aerial robot to navigate in different environments and carryi...

Nonlinear 3-D Motion Simulation Using Multi-Sensor Data Fusion

It is a interesting topic of tracking a 3D object and estimating its 3-D motion in a multi-sensor observation environment. The motion with constant translation velocity and constant rotation rate is assumed and tracked by two separate cameras. Hence the problem considered here also involves a track-to-track fusion system in which twosensors are tracking the same target. Due to the nonlinear nat...

Coverage Quality in Visual Sensor Networks

Flood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique

Floods are among the natural disasters that cause human hardship and economic loss. Establishing a viable flood forecasting and warning system for communities at risk can mitigate these adverse effects. However, establishing an accurate flood forecasting system is still challenging due to the lack of knowledge about the effective variables in forecasting. The present study has indicated that th...