Results 1 to 10 of about 93,046 (267)
The Megopolis resampler: Memory coalesced resampling on GPUs [PDF]
Digital Signal Processing, 2022 The resampling process employed in widely used methods such as Importance Sampling (IS), with its adaptive extension (AIS), are used to solve challenging problems requiring approximate inference; for example, non-linear, non-Gaussian state estimation problems.
Joshua A. Chesser +2 more
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Computers, 2023 Machine Learning is widely used in cybersecurity for detecting network intrusions. Though network attacks are increasing steadily, the percentage of such attacks to actual network traffic is significantly less.
Sikha S. Bagui +3 more
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Detection of Credit Card Fraud with Machine Learning Methods and Resampling Techniques
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022 Financial institutions in the form of banks provide facilities in the form of credit cards, but with the development of technology, fraud on credit card transactions is still common, so a system is needed that can detect fraud transactions quickly and ...
Moh. Badris Sholeh Rahmatullah +4 more
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Applied Sciences, 2022 Land use/land cover (LULC) has an important impact on the ecological environment and is crucial for calculating ecosystem service values (ESVs). However, whether and to what extent the ESVs vary when calculated by LULC product data at different spatial ...
Ziwen Huo +3 more
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Revealing Traces of Image Resampling and Resampling Antiforensics [PDF]
Advances in Multimedia, 2017 Image resampling is a common manipulation in image processing. The forensics of resampling plays an important role in image tampering detection, steganography, and steganalysis. In this paper, we proposed an effective and secure detector, which can simultaneously detect resampling and its forged resampling which is attacked by antiforensic schemes.
Anjie Peng, Yadong Wu, Xiangui Kang
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IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2023 Cardiovascular disease (CVD) is the leading cause of death worldwide. Primary prevention is by early prediction of the disease onset. Using laboratory data from the National Health and Nutrition Examination Survey (NHANES) in 2017-2020 timeframe (N= 7 ...
Fadlan Hamid Alfebi, Mila Desi Anasanti
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Fingerprint resampling: A generic method for efficient resampling [PDF]
Scientific Reports, 2015 AbstractIn resampling methods, such as bootstrapping or cross validation, a very similar computational problem (usually an optimization procedure) is solved over and over again for a set of very similar data sets. If it is computationally burdensome to solve this computational problem once, the whole resampling method can become unfeasible.
Mestdagh, Merijn +3 more
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GEOSTATISTICAL MODELING OF SOYBEAN YIELD AND SOIL CHEMICAL ATTRIBUTES USING SPATIAL BOOTSTRAP [PDF]
Engenharia AgrÃcola, 2019 The goal of this study was to use the spatial bootstrap method to model the spatial dependence structure of soybean yield and soil chemical attributes in an agricultural area.
Gustavo H. Dalposso +4 more
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The Chopthin Algorithm for Resampling [PDF]
IEEE Transactions on Signal Processing, 2016 14 pages, 4 ...
Axel Gandy, F. Din-Houn Lau
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Remote Sensing, 2023 Geostationary satellite-based remote sensing is a powerful tool to observe and understand the spatiotemporal variation of cloud optical-microphysical properties and their climatologies.
Dongchen Li, Masanori Saito, Ping Yang
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