Neocognitron: application to the handwritten Hindi numerals

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

Character recognition is a very important application in the field of computer vision. The neocognitron is a multilayered neural network, originally designed by Fakushima, that has the capbility of pattern recognition. Performance of the Neocognitron is not affected by translation, scaling, or deformation of the patterns. The objective of this thesis is to design the Neocognitron to recognize the handwirtten Hindi numerals. A proper training set was designed that consisted of features to be recognized at every layer. In addition, detailed analyses were carried out to decide on proper parameter assignments. A recognition rate of 95% was achieved with a 5% error rate compared to a 16% error rate reported by Fukushima. The designed Neocognitron maintains excellent performance under noisy environment. At 3 SNR, the Neocognitron maintains a recognition rate of not less than 85%.

روابط وملفات

التعريف والنوع

رقم الوثيقة

ec06ba6a-9398-4252-9230-0cd0cf0decde

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

944563_1.pdf

بيانات النشر

ترجمة العنوان

تطبيق ال Neocognitron على الأرقام الهندية

ألقاب المؤلفين

[{"name_ar":" Meng Er","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"تامبي محمد شريف بك","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

English

المصدر والدورية

اسم المصدر

Neocognitron: application to the handwritten Hindi numerals

المحتوى والصفحات

عدد الصفحات

0

إشراف وإعداد

الإشراف

Meng Er

الإعداد

تامبي محمد شريف بك

الاقتباسات الببليوغرافية