Performance evaluation of multi-sensor data fusion technique for test range application

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...

Multi-sensor Data Fusion for Future Telematics Application

In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information. The well-determined acquisition of vehicle’s position plays a vital role in application service. The development of GPS is used to provide the navigation data, but the performance is limited in areas where poor satell...

Multi-sensor data fusion using Bayesian programming : an automotive application

Data Synchronization Strategies for Multi-sensor Fusion

Advanced driver assistance systems (ADAS) have increasing demand for several sensor systems. Fusing multi-sensor data enlarges the field of view and increases the certainty and precision of the estimates. A crucial part of a fusion system is the data association, which requires data synchronization. The major synchronization strategies for data fusion are discussed and contrasted with respect t...

Multi sensor data fusion for change detection

When performing post-classification comparison using images of different sensors, change detection is still possible even if images have different resolutions. However, in this case, change pixels are detected in the pixel size of coarser resolution image. This problem can be solved using higher resolution aerial photographs or panchromatic images if available. In multi sensor image fusion, ima...