An Enhancement of Deep Face Technique Using Neural Network
نویسندگان
چکیده
منابع مشابه
INFLUENCE OF FIBER ASPECT RATIO ON SHEAR CAPACITY OF DEEP BEAMS USING ARTIFICIAL NEURAL NETWORK TECHNIQUE
This paper deals with the effect of fiber aspect ratio of steel fibers on shear strength of steel fiber reinforced concrete deep beams loaded with shear span to depth ratio less than two using the artificial neural network technique. The network model predicts reasonably good results when compared with the equation proposed by previous researchers. The parametric study invol...
متن کاملscour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
Face Recognition based on Deep Neural Network
In modern life, we see more techniques of biometric features recognition have been used to our surrounding life, especially the applications in telephones and laptops. These biometric recognition techniques contain face recognition, fingerprint recognition and iris recognition. Our work focuses on the face recognition problem and uses a deep learning method, convolutional neural network, to sol...
متن کاملA generalized ABFT technique using a fault tolerant neural network
In this paper we first show that standard BP algorithm cannot yeild to a uniform information distribution over the neural network architecture. A measure of sensitivity is defined to evaluate fault tolerance of neural network and then we show that the sensitivity of a link is closely related to the amount of information passes through it. Based on this assumption, we prove that the distribu...
متن کاملassessment of the efficiency of s.p.g.c refineries using network dea
data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...
ذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Signal Processing, Image Processing and Pattern Recognition
سال: 2016
ISSN: 2005-4254,2005-4254
DOI: 10.14257/ijsip.2016.9.8.25