— This paper describes an approach to cooperative localization which finds its roots in robust estimation, employing an unknown-but-bounded error model for sensor measurements. ...
Machine learning approaches to indoor WiFi localization involve an offline phase and an online phase. In the offline phase, data are collected from an environment to build a local...
Sinno Jialin Pan, Dou Shen, Qiang Yang, James T. K...
In this paper we analyze three well-known preprocessors for Max-SAT. The first preprocessor is based on the so-called variable saturation. The second preprocessor is based on the ...
In the case of multicomponent AM-FM signals, the idealized representation which consists of weighted trajectories on the time-frequency (TF) plane, is intrinsically sparse. Recent...
Most successful object recognition systems rely on binary classification, deciding only if an object is present or not, but not providing information on the actual object location...
Christoph H. Lampert, Matthew B. Blaschko, Thomas ...