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In this paper, we propose an adaptive constant false alarm detection method based on background Discrimination (BBD-CFAR) to address the issues of degraded ...
ABSTRACT. In this paper, we propose an adaptive constant false alarm detection method based on background. Discrimination (BBD-CFAR) to address the issues ...
This paper treats tracking as a foreground/background classification problem and proposes an online semi- supervised learning framework. Initialized with a ...
In this paper, a novel truncated statistics- and neural network-based CFAR (TSNN-CFAR) algorithm is developed.
The new detector is called SM-CFAR (Statistical Moments - CFAR) and is based on the square of the Mahalanobis distance.
Jun 6, 2022 · CFAR detection algorithm compares the gray value of each pixel in the SAR image with the adaptive detection threshold so that the target pixel ...
Therefore, to solve these problems, this paper proposes a novel deep learning network called “ShadowDeNet” for better shadow detection of moving ground targets ...
The invention relates to an average constant false alarm detection method of an intelligent reference unit, which comprises the following steps as shown in ...
CFAR detection is a term for methods that generate adaptive thresholds, and maintains a constant probability of false alarm. Consider a fixed threshold in a ...
This paper presents a target detection method for Synthetic Aperture Radar (SAR) image based on feature classification discrimination. Constant false alarm ...