ABSTRACT: Aiming at the problems of intensity inhomogeneity, boundary blurring and noise interference in the segmentation of three-dimensional volume data (such as medical images and industrial CT ...
ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...
In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...
Driven by a Vision to Deliver Smarter, Longer-Lasting Energy Solutions, Flux Power Integrates AI and Software Intelligence to Meet the Growing Demand for Adaptive, Data-Driven Electrification VISTA, ...
VISTA, Calif.--(BUSINESS WIRE)--Flux Power Holdings, Inc. (NASDAQ: FLUX), a leading developer of advanced lithium-ion energy storage solutions and software-driven electrification for commercial and ...
Reddit shares fell more than 15% on Wednesday after the company reported weaker-than-expected user numbers in its fourth-quarter earnings. Global daily active uniques, or DAUq, rose 39% from a year ...
Please see our online documentation here. This document provides only a brief overview. As an additional resource a web interface is provided, including an example dataset, here. Expectation ...
This article introduces a model-based design, implementation, deployment, and execution methodology, with tools supporting the systematic composition of algorithms from generic and domain-specific ...
Graph theory is an integral component of algorithm design that underlies sparse matrices, relational databases, and networks. Improving the performance of graph algorithms has direct implications to ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results