Development of a system for determination of different types of white blood corpuscle (Leucocyte) in dried blood smear
Başlık çevirisi mevcut değil.
- Tez No: 364419
- Danışmanlar: DOÇ. DR. H. ÖZCAN GÜLÇÜR
- Tez Türü: Yüksek Lisans
- Konular: Tıbbi Biyoloji, Medical Biology
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1991
- Dil: İngilizce
- Üniversite: Boğaziçi Üniversitesi
- Enstitü: Biyomedikal Mühendislik Enstitüsü
- Ana Bilim Dalı: Biyomedikal Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: Belirtilmemiş.
Özet
Özet yok.
Özet (Çeviri)
The networks which are composed of tightly connected simple processing elements and try to mimic the characteristics of the human brain such as massive parallelism, fault tolerance and learning from experience, are called artificial neural networks. In this thesis, artificial neural networks were examined and a software for recognizing white blood corpuscle was developed by using Kohonen's Self Organization Feature Map (S.O.F.M.) and perceptron algorithms. The S.O.F.M algorithm imitates the ordering of sensory pathways and the high level of organization created during learning in the human brain. In the present thesis digital white blood corpuscle images were processed by this algorithm and a feature vector was obtained. The resulting reduced feature vector is inputted to single-layer perceptron to train it's weights. After the training, the weights of the two algorithm was linked serially to make a final classification.
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