Study on Sperm-Cell Detection Using YOLOv5 Architecture with Labaled Dataset
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F23%3A50020215" target="_blank" >RIV/62690094:18450/23:50020215 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2073-4425/14/2/451" target="_blank" >https://www.mdpi.com/2073-4425/14/2/451</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/genes14020451" target="_blank" >10.3390/genes14020451</a>
Alternative languages
Result language
angličtina
Original language name
Study on Sperm-Cell Detection Using YOLOv5 Architecture with Labaled Dataset
Original language description
Infertility has recently emerged as a severe medical problem. The essential elements in male infertility are sperm morphology, sperm motility, and sperm density. In order to analyze sperm motility, density, and morphology, laboratory experts do a semen analysis. However, it is simple to err when using a subjective interpretation based on laboratory observation. In this work, a computer-aided sperm count estimation approach is suggested to lessen the impact of experts in semen analysis. Object detection techniques concentrating on sperm motility estimate the number of active sperm in the semen. This study provides an overview of other techniques that we can compare. The Visem dataset from the Association for Computing Machinery was used to test the proposed strategy. We created a labelled dataset to prove that our network can detect sperms in images. The best not-super tuned result is mAP (Formula presented.). © 2023 by the authors.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Genes
ISSN
2073-4425
e-ISSN
2073-4425
Volume of the periodical
14
Issue of the periodical within the volume
2
Country of publishing house
CH - SWITZERLAND
Number of pages
14
Pages from-to
"Article number: 451"
UT code for WoS article
000945699200001
EID of the result in the Scopus database
2-s2.0-85148882863