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Träfflista för sökning "WFRF:(Campos Alexandre Becker 1997 ) "

Sökning: WFRF:(Campos Alexandre Becker 1997 )

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1.
  • Campos, Alexandre Becker, 1997-, et al. (författare)
  • False Alarm Reduction in Wavelength-Resolution SAR Change Detection Schemes by Using a Convolutional Neural Network
  • 2022
  • Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19
  • Tidskriftsartikel (refereegranskat)abstract
    • In this letter, we propose a method to reduce the number of false alarms in a wavelength-resolution synthetic aperture radar (SAR) change detection scheme by using a convolutional neural network (CNN). The detection is performed in two steps: change analysis and object classification. A simple technique for wavelength-resolution SAR change detection is implemented to extract potential targets from the image of interest. A CNN is then used for classifying the change map detections as either a target or nontarget, further reducing the false alarm rate (FAR). The scheme is tested for the CARABAS-II data set, where only three false alarms over a testing area of 96 km² are reported while still sustaining a probability of detection above 96%. We also show that the network can still reduce the FAR even when the flight heading of the SAR system measurement campaign differs by up to 100° between the images used for training and test. CCBY
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2.
  • Campos, Alexandre Becker, 1997-, et al. (författare)
  • UNSUPERVISED AUTOMATIC TARGET DETECTION FOR MULTITEMPORAL SAR IMAGES BASED ON ADAPTIVE K-MEANS ALGORITHM
  • 2020
  • Konferensbidrag (refereegranskat)abstract
    • In this paper, we present an unsupervised automatic target detection algorithm for multitemporal SAR images. The proposed two-fold method is expected to reduce processing time for large scene sizes with sparse targets while still improving detection performance. Firstly, pixel blocks are extracted from an initial change map to reduce the algorithm's search space and favor target detection. Secondly, an adaptive k-means algorithm selects the number of clusters that better separates targets from false alarms, which are discarded. Preliminary results show the advantages of the proposed method in processing time and detection performance over a recently proposed supervised method for the CARABAS-II dataset.
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  • Resultat 1-2 av 2
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refereegranskat (2)
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Machado, Renato (2)
Pettersson, Mats, 19 ... (2)
Vu, Viet Thuy, 1977- (2)
Campos, Alexandre Be ... (2)
Molin, Ricardo (1)
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Blekinge Tekniska Högskola (2)
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Engelska (2)
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