Rigid Shape Registration Based on Extended Hamiltonian Learning.

Jin Yi, Shiqiang Zhang, Yueqi Cao, Erchuan Zhang, Huafei Sun

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Image Registration for Visualizing Magnetic Flux Leakage Testing under Different Orientations of Magnetization.Entropy (Basel, Switzerland) · 2023
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.

Jin YiDepartment of Basic Courses, Beijing Union University, Beijing 100081, China.ORCID 0000-0003-0579-8990

Shiqiang ZhangSchool of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China.

Yueqi CaoSchool of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China.ORCID 0000-0001-8856-2902

Erchuan ZhangSchool of Mathematics and Statistics, University of Western Australia, Crawley WA6009, Australia.

Huafei SunSchool of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China.

Funding

National Natural Science Foundation of China 61179031

6 · The paper itself

Abstract

Shape registration, finding the correct alignment of two sets of data, plays a significant role in computer vision such as objection recognition and image analysis. The iterative closest point (ICP) algorithm is one of well known and widely used algorithms in this area. The main purpose of this paper is to incorporate ICP with the fast convergent extended Hamiltonian learning (EHL), so called

Indexed as

extended Hamiltonian learningiterative closest pointrigid registrationspecial Euclidean group

Identifiers

PMID33286311

DOI10.3390/e22050539

PMCPMC7517035

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

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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.