Evidence map›Paper›PMID 34778731›Full record

ArticleiScience2021

Deep learning enhanced terahertz imaging of silkworm eggs development.

Hongting Xiong, Jiahua Cai, Weihao Zhang, Jingsheng Hu, Yuexi Deng, Jungang Miao, Zhiyong Tan, Hua Li, Juncheng Cao, Xiaojun Wu

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

Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

4 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Automated Prototype forSensors (Basel, Switzerland) · 2023
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  4. Review
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

10 authors at 4 institutions in 1 country.

Hongting XiongSchool of Electronic and Information Engineering, Beihang University, Beijing 100191, China.
Jiahua CaiSchool of Electronic and Information Engineering, Beihang University, Beijing 100191, China.
Weihao ZhangSchool of Cyber Science and Technology, Beihang University, Beijing 100191, China.
Jingsheng HuCollege of Engineering, Peking University, Beijing 100191, China.
Yuexi DengCollege of Engineering, Peking University, Beijing 100191, China.
Jungang MiaoSchool of Electronic and Information Engineering, Beihang University, Beijing 100191, China.
Zhiyong TanKey Laboratory of Terahertz Solid State Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050 China.
Hua LiKey Laboratory of Terahertz Solid State Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050 China.
Juncheng CaoKey Laboratory of Terahertz Solid State Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050 China.
Xiaojun WuSchool of Electronic and Information Engineering, Beihang University, Beijing 100191, China.
Beihang University · CNShanghai Institute of Microsystem and Information Technology · CNPeking University · CNWuhan National Laboratory for Optoelectronics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Terahertz (THz) technology lays the foundation for next-generation high-speed wireless communication, nondestructive testing, food safety inspecting, and medical applications. When THz technology is integrated by artificial intelligence (AI), it is confidently expected that THz technology could be accelerated from the laboratory research stage to practical industrial applications. Employing THz video imaging, we can gain more insights into the internal morphology of silkworm egg. Deep learning algorithm combined with THz silkworm egg images, rapid recognition of the silkworm egg development stages is successfully demonstrated, with a recognition accuracy of ∼98.5%. Through the fusion of optical imaging and THz imaging, we further improve the AI recognition accuracy of silkworm egg development stages to ∼99.2%. The proposed THz imaging technology not only features the intrinsic THz imaging advantages, but also possesses AI merits of low time consuming and high recognition accuracy, which can be extended to other application scenarios.

Indexed as

Applied physicsMachine learningWave imaging

Identifiers

PMID34778731
PMCPMC8577140
OpenAlexW3206421335

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.