Buried-object detection using free-space time-domain near-field measurements
نویسندگان
چکیده
منابع مشابه
Near-field microscope probe for far infrared time domain measurements
A near-field probe fabrication technique for far-infrared frequencies based on photoconducting antennas is developed. A subwavelength-size field source is accomplished by means of an aperture and protruding high refractive index tip. The near-field probe is tested by using free space traveling electromagnetic pulses with a broadband spectrum in the range of 0.3–1.5 THz. A spatial resolution of ...
متن کاملFree Space Estimation using Occupancy Grids and Dynamic Object Detection
In this paper we present an approach to estimate Free Space from a Stereo image pair using stochastic occupancy grids. We do this in the domain of autonomous driving on the famous benchmark dataset KITTI. Later based on the generated occupancy grid we match 2 image sequences to compute the top view representation of the map. We do this to map the environment. We compute a transformation between...
متن کاملAn innovative real-time technique for buried object detection
In this paper, a new on-line inverse scattering methodology is proposed. The original problem is recast into a regression estimation one and successively solved by means of a support vector machine (SVM). Although the approach can be applied to various inverse scattering applications, it results very suitable to deal with the buried object detection. The application of SVMs to the solution of s...
متن کاملNewborn EEG Seizure Detection Based on Interspike Space Distribution in the Time-Frequency Domain
This paper presents a new time-frequency based EEG seizure detection method. This method uses the distribution of interspike intervals as a criterion for discriminating between seizure and nonseizure activities. To detect spikes in the EEG, the signal is mapped into the time-frequency domain. The high instantaneous energy of spikes is reflected as a localized energy in time-frequency domain. Hi...
متن کاملCombined Object Detection and Segmentation by Using Space-Time Patches
This paper presents a method for classifying the direction of movement and for segmenting objects simultaneously using features of space-time patches. Our approach uses vector quantization to classify the direction of movement of an object and to estimate its centroid by referring to a codebook of the space-time patch feature, which is generated from multiple learning samples. We segmented the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Microwave and Optical Technology Letters
سال: 2001
ISSN: 0895-2477,1098-2760
DOI: 10.1002/mop.1352