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Feature extraction for automatic classification of EEG signals typically relies on time frequency representations of the signal. Techniques such as cepstral-based filter banks or wavelets are popular analysis techniques in many signal processing applications including EEG classification. In this paper, we present a comparison of a variety of approaches to estimating and postprocessing features. To...
The Neural Engineering Data Consortium (NEDC) is releasing its first major big data corpus — the Temple University Hospital EEG Corpus. This corpus consists of over 25,000 EEG studies, and includes a neurologist's interpretation of the test, a brief patient medical history and demographic information about the patient such as gender and age. For the first time, there is a sufficient amount of data...
The recently established Neural Engineering Data Consortium (NEDC) is in the process of developing its first large-scale corpus. This corpus, known as the Temple University Hospital EEG Corpus, upon completion, will total over 20,000 EEG studies, and include patient information, medical histories and physician assessments, making it the largest and most comprehensive publicly released EEG corpus....
This paper presents an incremental object part detection algorithm using a particle filter. The method infers object parts from 3D data acquired with a range camera. The range information is quantized and enhanced by local structure to partially cope with considerable measurement noise and distortion. The augmented voxel representation allows the adaptation of known track-before-detect algorithms...
Simple, fast and lightweight SLAM algorithms are necessary in many embedded robotic systems which soon will be used in houses and offices in order to do various service tasks. In this paper the Orthogonal SLAM algorithm is presented as an answer to this need. In continuation of our previous work, the algorithm is extended to generate 3D maps and empirically validated by mapping the long corridor of...
Toward obtaining a compact and multiresolution representation of 2D range scans, a wavelet framework is proposed for encoding an orientation measure called running angle (RA). A new shrinkage algorithm is developed using discrete wavelet transform of the RA signal, which leads to a simplified polyline approximation of the initial scanned points. This approach is evaluated in terms of segmentation...
In this paper, we describe a new approach for the extrinsic calibration of a camera with a 3D laser range finder, that can be done on the fly. This approach does not require any calibration object. Only few point correspondences are used, which are manually selected by the user from a scene viewed by the two sensors. The proposed method relies on a novel technique to visualize the range information...
Today, lightweight SLAM algorithms are needed in many embedded robotic systems. In this paper the orthogonal SLAM (OrthoSLAM ) algorithm is presented and empirically validated. The algorithm has constant time complexity in the state estimation and is capable to run real-time. The main contribution resides in the idea of reducing the complexity by means of an assumption on the environment. This is...
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