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The details will be discussed in Section 2. In [19], new approaches for localization have been introduced.
Our results demonstrate the utility of combining subcellular fractionation, proteomic analysis, and bioinformatic approaches for localization of organellar proteins that are difficult to detect with whole cell methodologies.
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This paper presents an image-based approach for localization in non-static environments using local feature descriptors, and its experimental evaluation in a large, dynamic, populated environment where the time interval between the collected data sets is up to two months.
This paper describes a novel approach for localization of multiple sources overlapping in time.
We have presented a new approach for localization in a realistic indoor environment, where multipath fading is highly present.
Theoretical analysis and experimental data will be used to motivate and justify the pursuit of the proposed approach for localization in a dispersive medium.
This paper presents an approach for localization using geometric features from a 360° laser range finder and a monocular vision system.
Experiments with SPARUS II in simulated environments show the improvement and benefits in the application of this SLAM approach for localization, navigation and control, with respect to the use of the EKF odometry.
The range-based time of arrival (TOA) approach is the most suitable approach for localization in UWB sensor networks, because it is proved to have a very good accuracy due to the high time resolution (large bandwidth) of UWB signals [3, 4].
It is well assumed in the literature that approaches for the localization of vacant spectrum bands based exclusively on local sensing and learning do not offer satisfactory results [3,4].
We introduce a new approach for proving localization (pure point spectrum with exponentially decaying eigenfunctions, dynamical localization) for the Anderson model at high disorder.
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