Setyawan, Dimas Arif (2022) Klasifikasi Morfologi Kepala Spermatozoa Manusia Dengan Algoritma Convolutional Neural Network Arsitektur MobileNet. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
Infertility is a symptom of infertility or infertility after a couple has been married for a long time but the wife never shows signs of getting a pregnancy. Infertility can occur in both women and men. Infertility in men is caused by poor quality of spermatozoa or abnormalities in spermatozoa. With the current Computer-aided Sperm Analysis (CASA) technology, sperm quality examination in men can use artificial intelligence technology. In this study, the method implemented in developing the examination is Convolutional Neural Network with MobileNet architecture which is a type of development algorithm from artificial neural network algorithms in classifying. The data used in this study are 3000 images which have 3 classes to be classified, namely Abnormal Sperm, Non Sperm, and Normal Sperm. The performance of the learning model from the test results in the research is contained in the MobileNet architecture with a fine tuning approach on the last 7 layers. The learning model on the architecture can achieve an accuracy of 88%.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | T Technology > T Technology (General) | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | DIMAS ARIF SETYAWAN | ||||||||||||
| Date Deposited: | 29 Jul 2022 07:26 | ||||||||||||
| Last Modified: | 29 Jul 2022 07:26 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/8531 |
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