Evidence map›Paper›PMID 37514315›Full record

ArticlePlants (Basel, Switzerland)2023

Classification of

Yixin Chen, Xiyun Wang, Zhibo Chen, Kang Wang, Ye Sun, Jiarong Jiang, Xuhao Liu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plants (Basel, Switzerland), 2023. 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
2.4field-weighted citation impact, top 11% of its field
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, 6 citations in OpenAlex.

  1. Review
  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

7 authors at 1 institution in 1 country.

Yixin ChenSchool of Information Science and Technology, Beijing Forestry University, No. 35 Qinghuadong Road, Beijing 100083, China.ORCID 0000-0001-8339-222X
Xiyun WangSchool of Information Science and Technology, Beijing Forestry University, No. 35 Qinghuadong Road, Beijing 100083, China.
Zhibo ChenSchool of Information Science and Technology, Beijing Forestry University, No. 35 Qinghuadong Road, Beijing 100083, China.
Kang WangSchool of Information Science and Technology, Beijing Forestry University, No. 35 Qinghuadong Road, Beijing 100083, China.
Ye SunSchool of Information Science and Technology, Beijing Forestry University, No. 35 Qinghuadong Road, Beijing 100083, China.
Jiarong JiangSchool of Information Science and Technology, Beijing Forestry University, No. 35 Qinghuadong Road, Beijing 100083, China.
Xuhao LiuSchool of Biological Sciences and Biotechnology, Beijing Forestry University, No. 35 Qinghuadong Road, Beijing 100083, China.
Beijing Forestry University · CN

Funding

Beijing Forestry University's Action Plan for Scientific Research and Entrepreneurship among University Students No. S202110022127Research and Development of Distributed Forestry and Grass Science and Technology Extension System 2021BLRD06
6 · The paper itself

Abstract

The use of neural networks for plant disease identification is a hot topic of current research. However, unlike the classification of ordinary objects, the features of plant diseases frequently vary, resulting in substantial intra-class variation; in addition, the complex environmental noise makes it more challenging for the model to categorize the diseases. In this paper, an attention and multidimensional feature fusion neural network (AMDFNet) is proposed for

Indexed as

attention mechanismCamellia oleifera diseases classificationconvolutional neural networksfeature fusion

Identifiers

PMID37514315
PMCPMC10386666
OpenAlexW4384929871

What OpenQuestion holds

Textmetadata
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.