Evidence map›Paper›PMID 33265342›Full record

ArticleEntropy (Basel, Switzerland)2018

A Novel Fractional-Order Chaotic Phase Synchronization Model for Visual Selection and Shifting.

Xiaoran Lin, Shangbo Zhou, Hongbin Tang, Ying Qi, Xianzhong Xie

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xiaoran LinCollege of Computer Science, Chongqing University, Chongqing 400044, China.
Shangbo ZhouCollege of Computer Science, Chongqing University, Chongqing 400044, China.
Hongbin TangCollege of Computer Science, Chongqing University, Chongqing 400044, China.
Ying QiCollege of Computer Science, Chongqing University, Chongqing 400044, China.
Xianzhong XieChongqing/MII Key Lab. of Computer Network and Communication Technology, Chongqing 400044, China.

Funding

NIAAA NIH HHS L30 AA015308
6 · The paper itself

Abstract

Visual information processing is one of the fields of cognitive informatics. In this paper, a two-layer fractional-order chaotic network, which can simulate the mechanism of visual selection and shifting, is established. Unlike other object selection models, the proposed model introduces control units to select object. The first chaotic network layer of the model is used to implement image segmentation. A control layer is added as the second layer, consisting of a central neuron, which controls object selection and shifting. To implement visual selection and shifting, a strategy is proposed that can achieve different subnets corresponding to the objects in the first layer synchronizing with the central neuron at different time. The central unit acting as the central nervous system synchronizes with different subnets (hybrid systems), implementing the mechanism of visual selection and shifting in the human system. The proposed model corresponds better with the human visual system than the typical model of visual information encoding and transmission and provides new possibilities for further analysis of the mechanisms of the human cognitive system. The reasonability of the proposed model is verified by experiments using artificial and natural images.

Indexed as

active controlchaotic phase synchronizationcognitive informaticsfractional-order

Identifiers

PMID33265342
PMCPMC7512766

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.