Sperm-cell Detection Using YOLOv5 Architecture
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F22%3A50019256" target="_blank" >RIV/62690094:18450/22:50019256 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-07802-6_27" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-07802-6_27</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-07802-6_27" target="_blank" >10.1007/978-3-031-07802-6_27</a>
Alternative languages
Result language
angličtina
Original language name
Sperm-cell Detection Using YOLOv5 Architecture
Original language description
Infertility has become a severe health issue in recent years. Sperm morphology, sperm motility, and sperm density are the most critical factors in male infertility. As a result, sperm motility, density, and morphology are examined in semen analysis carried out by laboratory professionals. However, applying a subjective analysis based on laboratory observation is easy to make a mistake. To reduce the effect of specialists in semen analysis, a computer-aided sperm count estimation approach is proposed in this work. The quantity of active sperm in the semen is determined using object detection methods focusing on sperm motility. The proposed strategy was tested using data from the Visem dataset provided by Association for Computing Machinery. We created a small sample custom dataset to prove that our network will be able to detect sperms in images. The best not-super tuned result is mAP 72.15. © 2022, Springer Nature Switzerland AG.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-3-031-07801-9
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
12
Pages from-to
319-330
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Švýcarsko
Event location
Grand Canaria
Event date
Jun 27, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000871766000027