Titlebook: Radiation Therapy of Benign Diseases; A Clinical Guide Stanley E. Order,Sarah S. Donaldson Book 19901st edition Springer-Verlag Berlin Heid

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Stanley E. Order MD, ScD, FACR,Sarah S. Donaldson MD, FACRN model often requires very intensive computational resources. For edge incremental learning, more energy efficient learning solutions are called for. Heterogeneous computing is more power efficient, and has been increasingly popular for embedded platforms. Therefore, how to deploy training models o

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Stanley E. Order MD, ScD, FACR,Sarah S. Donaldson MD, FACRShor’s algorithm is expected in the near-to-medium future. Lattice-based PQC algorithms are among the most promising candidates discussed today, due to their performance and versatility. In this paper, we demonstrate fault sensitivity analysis (FSA) of circuit blocks used in lattice-based cryptograp

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Stanley E. Order MD, ScD, FACR,Sarah S. Donaldson MD, FACRared to a cloud solution. As most edge devices are memory- and compute-constrained, they cannot store and execute a complete Deep Neural Network (DNN). One possible solution is to distribute the DNN across multiple edge devices. For a complete distribution, both fully-connected and feature- and weig

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Stanley E. Order MD, ScD, FACR,Sarah S. Donaldson MD, FACRShor’s algorithm is expected in the near-to-medium future. Lattice-based PQC algorithms are among the most promising candidates discussed today, due to their performance and versatility. In this paper, we demonstrate fault sensitivity analysis (FSA) of circuit blocks used in lattice-based cryptograp

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Stanley E. Order MD, ScD, FACR,Sarah S. Donaldson MD, FACRon pipeline from image acquisition to result output, including the operations that are to be performed on the images. This chapter gives an overview of this pipeline and the involved hardware components. It discusses several types of image sensors as well as their readout styles, speeds, and interfa

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Stanley E. Order MD, ScD, FACR,Sarah S. Donaldson MD, FACRion tasks, such as camera calibration and visual object recognition. In particular, the driving force was the development of new powerful algorithms, especially in the area of local features. On the other hand, embedded vision platforms and solutions, such as smart cameras, have successfully emerged