مشروع البحث:
FACIAL EMOTION IMAGES RECOGNITION BASED ON BINARIZED GENETIC ALGORITHM-RANDOM FOREST

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المساهمين
الممولين
رقم التعريف
711
الباحث
مراد ابراهيم حسين الثابت
المشرفين
منشورات
وحدات تنظيمية
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وحدة تنظيمية
الوصف
This thesis proposed a facial emotion recognition system based on HOG features and BGA-RF features selection. The study developed a facial emotion recognition system based on HOG features and BGA which has been utilized as a features selection in order to select the most effective features of HOG. Besides, the RF was used as a classifier to classify human facial emotions based on images samples. The input consisted of a set of 11 common human facial emotions which are centre light, glasses, happy, left light, no glasses, normal, right light, sad, sleepy, surprised, and wink with the output being the class to which the utterance was associated with or related to.
الكلمات الدالة
GENETIC ALGORITHM-RANDOM FOREST