Results 151 to 160 of about 20,157 (304)

On integer linear programming.

open access: yes, 1968
A survey of the methods of solving the integer program, max summation from j=1 to j=n of the quantity (c sub j x sub j) subject to summation, j=1 to j=n of the quantity (a sub ij x sub j) = b sub i, i=1,...,m, and x sub j = or 0 and integer (j=1,...,n) is presented. Emphasis is placed on methods developed since 1960 with many as yet unpublished methods
openaire   +1 more source

Gaussian Mixture Model‐Based Data Association Incorporating a Deep Learning Network for Multivehicle Tracking and Detection in Autonomous Driving Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a real‐time light detection and ranging‐camera fusion framework for vehicle detection and tracking. Using a Gaussian mixture model‐based association and improved affinity metrics, the method enhances tracking reliability in dynamic conditions.
Muhammad Adeel Altaf, Min Young Kim
wiley   +1 more source

Neural Networks for Encoding Dynamic Security-Constrained Optimal Power Flow to Mixed-Integer Linear Programs. [PDF]

open access: green, 2020
Andreas Venzke   +4 more
openalex  

Memory‐Reduced Convolutional Neural Network for Fast Phase Hologram Generation

open access: yesAdvanced Intelligent Systems, EarlyView.
This article reports a lightweight convolutional neural network framework using INT8 quantization to efficiently generate 3D computer‐generated holograms from a single 2D image. The quantized model reduces memory usage and computational cost, accelerates inference speed, and maintains high output quality, enabling real‐time holographic display on low ...
Chenliang Chang   +6 more
wiley   +1 more source

Long Reads Assembly Using Integer Linear Programming

open access: green, 2020
Victor Epain   +3 more
openalex   +1 more source

ORGANIZING BUSINESS FORUMS WITH INTEGER LINEAR PROGRAMMING

open access: gold, 2019
José Francisco Moreira Pessanha   +1 more
openalex   +1 more source

Home - About - Disclaimer - Privacy