Road Drift

Updating Road Network Databases: Road Segment Grouping Using Snap-Drift Neural Network

Updating of Road Network Databases: Spatio-Temporal Trajectory Grouping Using Snap-Drift Neural Network

Research towards an innovative solution to the problem of automated updating of road network databases is presented. It moves away from existing methods where vendors of road network databases either go through the time consuming and logistically challenging process of driving along roads to register changes or use update methods that rely on remote sensing images. The solution presented here w...

Spatiotemporal Kriging with External Drift

In statistics it is often assumed that sample observations are independent. But sometimes in practice, observations are somehow dependent on each other. Spatiotemporal data are dependent data which their correlation is due to their spatiotemporal locations.Spatiotemporal models arise whenever data are collected across bothtime and space. Therefore such models have to be analyzed in termsof thei...

drift correction technique

sensitivity of an electromagnetic type metal detector is directly related to stability, the higher the required sensitivity, the more frequently the rebalancing controls will have to be adjusted. thus, for maximum sensitivity in the head ,the use of automatic drift compensation network is necessary in order to cancel out the signal resulting from a slow drift in the coil system due to the tempe...

Concept Drift

Traditional approaches to data mining are based on an assumption that the process that generated or is generating a data stream is static. Although this assumption holds for many applications, it does not hold for many others. Consider systems that build models for identifying important e-mail. Through interaction with and feedback from a user, such a system might determine that particular e-ma...