Results 11 to 20 of about 26,379 (227)

GAN‐LSTM‐3D: An efficient method for lung tumour 3D reconstruction enhanced by attention‐based LSTM

open access: yesCAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Three‐dimensional (3D) image reconstruction of tumours can visualise their structures with precision and high resolution. In this article, GAN‐LSTM‐3D method is proposed for 3D reconstruction of lung cancer tumours from 2D CT images. Our method consists of three phases: lung segmentation, tumour segmentation, and tumour 3D reconstruction. Lung
Lu Hong   +12 more
wiley   +1 more source

Domain‐adapted driving scene understanding with uncertainty‐aware and diversified generative adversarial networks

open access: yesCAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua   +4 more
wiley   +1 more source

Implementasi Algoritma Minimax Pada Permainan Checker Berbasis Artificial Intelligence [PDF]

open access: yes, 2023
Permainan (game)sering memanfaatkan kecerdasan buatan(Artificial Intelligence) untuk memberikan tantangan berupa kesempatan untuk melawan mesin yang memiliki tingkat intelektualitas tertentu dalam berpikir.
Masri, Mahrizal   +3 more
core   +1 more source

On the minimax spherical designs

open access: yesRandom Structures & Algorithms, 2022
AbstractDistributing points on a (possibly high‐dimensional) sphere with minimal energy is a long‐standing problem in and outside the field of mathematics. This paper considers a novel energy function that arises naturally from statistics and combinatorial optimization, and studies its theoretical properties.
Weibo Fu, Guanyang Wang, Jun Yan
openaire   +2 more sources

Minimax Rényi redundancy [PDF]

open access: yes2017 IEEE International Symposium on Information Theory (ISIT), 2017
Double-column, 19 pages, submitted for publication to IEEE Transactions on Information Theory. Disclaimer: the published version may have slight variations.
Semih Yagli, Yucel Altug, Sergio Verdú
openaire   +4 more sources

An ordinal minimax theorem [PDF]

open access: yesGames and Economic Behavior, 2016
In the early 1950s Lloyd Shapley proposed an ordinal and set-valued solution concept for zero-sum games called \emph{weak saddle}. We show that all weak saddles of a given zero-sum game are interchangeable and equivalent. As a consequence, every such game possesses a unique set-based value.
Felix Brandt 0001   +2 more
openaire   +3 more sources

Minimax and Minimax Projection Designs Using Clustering [PDF]

open access: yesJournal of Computational and Graphical Statistics, 2017
Under revision, Journal of Computational and Graphical Statistics (JCGS)
Mak, Simon, Joseph, V. Roshan
openaire   +2 more sources

Minimax based congestion control for TCP network systems with UDP flows

open access: yesMATEC Web of Conferences, 2018
The congestion control problem for TCP network systems with UDP flows is considered. A nonlinear TCP network model with strict-feedback structure is established.
Jing Yuanwei   +2 more
doaj   +1 more source

A Class of Equations with Three Solutions

open access: yesMathematics, 2020
Here is one of the results obtained in this paper: Let Ω ⊂ R n be a smooth bounded domain, let q > 1 , with q λ 1 and for every convex set S ⊆ L ∞ ( Ω ) dense in L 2 ( Ω ) , there exists α ∈ S ...
Biagio Ricceri
doaj   +1 more source

Generative Adversarial Networks for Omics Data: An Overview and Future Directions for Livestock Applications. [PDF]

open access: yesAnim Genet
ABSTRACT Generative adversarial networks (GANs) are artificial intelligence models designed to generate novel data that is indistinguishable from real data. Originally developed to generate images to complement existing datasets and create more diverse samples, GAN‐based data can enhance downstream analysis for machine learning and deep learning ...
Vargas EC, Bresolin T.
europepmc   +2 more sources

Home - About - Disclaimer - Privacy