Results 241 to 250 of about 4,256,847 (295)
Robust Random Walk Based on Natural Neighbors for Outlier Detection. [PDF]
Chen K, Zhu W, Li T, Wang H.
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ADAPT-Net: an adaptive dynamic attention and persistence-aware transformer for overlapping community detection in complex social networks. [PDF]
Vusirikkayala G, Madhu Viswanatham V.
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Insight and executive functions in acquired brain injury: empirical evidence and theoretical frameworks. [PDF]
Sigala N +3 more
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Adaptive Convolution for Object Detection
IEEE Transactions on Multimedia, 2019It is quite challenging to detect objects, especially, small objects, in complex scenes. To solve this problem, we propose a novel module named as adaptive convolution block (ACB), which adaptively adjusts the parameters of convolutional filters according to the current feature maps, and then, filter these feature maps with the obtained adaptive ...
Qiang Ling, Chunlin Chen
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Adaptive Target Separation Detection
IEEE Transactions on Aerospace and Electronic Systems, 2021This article considers target separation detection (TSD) in the presence of homogeneous Gaussian interference. The problem is formulated as a hypothesis test for two typical situations: 1) the use of a low range-resolution radar or fast-track update rate; 2) the use of a high-resolution radar or low-track update rate. At the design stage, TSD tests are
Yongchan Gao +3 more
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Data Mining and Knowledge Discovery, 1997
One method for detecting fraud is to check for suspicious changes in user behavior. This paper describes the automatic design of user profiling methods for the purpose of fraud detection, using a series of data mining techniques. Specifically, we use a rule-learning program to uncover indicators of fraudulent behavior from a large database of customer ...
Tom Fawcett, Foster J. Provost
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One method for detecting fraud is to check for suspicious changes in user behavior. This paper describes the automatic design of user profiling methods for the purpose of fraud detection, using a series of data mining techniques. Specifically, we use a rule-learning program to uncover indicators of fraudulent behavior from a large database of customer ...
Tom Fawcett, Foster J. Provost
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Edge Detection by Adaptive Splitting
Journal of Scientific Computing, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bernardo Llanas, Sagrario LantarĂ³n
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Detectability in Conventional and Adaptive Sampling
Biometrics, 1994In this paper a simple but very general method is given for estimating a population total with any sampling design when objects in sampled units are observed with imperfect detectability--a problem characteristic of many surveys of natural and human populations.
Thompson, Steven K., Seber, George A. F.
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