Titlebook: Advanced Computing and Systems for Security: Volume 13; Rituparna Chaki,Nabendu Chaki,Khalid Saeed Book 2022 The Editor(s) (if applicable)

Monocle

BULLY

Rituparna Chaki,Nabendu Chaki,Khalid SaeedDiscusses recent research trends in computational intelligence.Presents applications to design, analysis, and modeling – key areas in computational intelligence.Explores efficient computational algori

小教堂

Lecture Notes in Networks and Systemshttp://image.papertrans.cn/a/image/145395.jpg

Lacunar-Stroke

Cpr951

https://doi.org/10.1057/9781137272867s (such as MPICH and Open MPI) have been broadly used in the high-performance computing area to provide efficient data processing. This paper investigates whether MPI can be adapted to a batch processing task in the field of image processing which has the characteristic of input and output data in t

Atmosphere

https://doi.org/10.1057/9781137272867with some added advantages like heterogeneous integration, higher computation per volume, etc. These benefits are also exhibited in 3D SoCs (3D System on Chips) to use the already built cores. However, testing these large complex SoCs in lesser time has become a challenge. In this paper, we propose

表脸

悠然

J. J. de la Rosette,F. M. Debruyned. Firstly, the images are pre-processed for further tasks which are followed by the extraction of morphological and amplitude-based features. The best discriminatory features are chosen by applying several feature selection techniques which evaluate the merit of a feature by assessing the goodness

大方不好

Klinische Diagnostik und PCA-Screeninguracy guaranteed by this measurable trait. In the literature, one can easily find diversified approaches and algorithms connected with this feature, however, neither of them uses discrete fast Fourier transform to describe iris sample. In this work, the authors used recently mentioned method to crea

LAVA

Klaus Höfner,Udo Jonas,Christian G. Stiefby them is maximized. In general, the performance of an influence maximization algorithm is measured in terms of solution accuracy and computational efficiency. Simulation-based greedy algorithms can achieve high solution accuracy but are inappropriate for large networks owing to their huge computat