Computer algorithms for scheduling and related problems in the theory of graphs / Selim, Said

, tensor decompositions are useful in machine learning, chemometrics, computer vision, graph analysis, and

algorithms to the point cloud. The result is a highly adjustable, generalized algorithm to convert raw point

. There are three different numerical algorithms namely the explicit, implicit, and hybrid schemes that

algorithms, various machine learning algorithms including deep neural networks, and optimal state estimator

Fields such as Computer Vision and Natural Language Processing have a high applicability of Machine

This dissertation explores computer vision algorithms to reconstruct 3D models from satellite

All the algorithms we present are evaluated on various benchmarks that are computer models of

In recent years, the field of computer vision has seen a series of major advances, made possible by

arbitrarily "draped" over the underlying processor fabric. Logically, this allows the computer architecture of

optimization problems. This thesis discusses experimental results for several quantum algorithms performed on a

-scale real-world datasets from different applications including computer vision, social media, health care

exponentiation based public-key cryptography algorithms. A new algorithm based on the Montgomery reduction method

digital filtering. There being several classes of digital filter, and in general many algorithms for

decomposition based algorithms for detecting inconsistent information in an unsupervised learning setting. In