Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes into account the majority of the challenges faced by existing methods of age estimate. Making use of the data set that serves as the foundation for the face estimation system in this region (IMDB-WIKI). By performing preparatory processing activities to setup and train the data in order to collect cases, and by using the CNN deep learning method, which yielded results with an accuracy of 0.960 percent, we were able to reach our objective.
Purpose: To evaluate the effect of intravitreal Aflibercept injection on wet AMD both functionally and anatomically after loading doses. The secondary aim is to evaluate the effect of risk factors including (gender, age, smoking, hypertension, and diabetes meatus) on the patient’s response. Study Design: Interventional case series. Place and Duration of Study: Al-Haitham Eyes Teaching Hospital in Baghdad, Iraq, from November 2021 and September 2022. Methods: Fifty eyes of 47 patients with treatment naïve wet AMD were selected through convenient sampling. Data were collected for age, gender, smoking, and chronic disease. Clinical examination, best corrected visual acuity (BCVA), optical coherence tomography angiography
... Show MoreABSTRACT Background: Dental caries is a most common social and intractable infectious disease in human. Saliva is critical for preserving and maintaining oral health and salivary elements had many effects on caries experience. Aim of study: This study was conducted to assess dental caries severity by age and gender and their relation to salivary zinc and copper among a group of adults aged (19-22) years. Materials and methods: After examination eighty persons aged 19-22 years of both gender. Caries severity was documented according to DMFS index. Stimulated salivary samples were collected and chemically analyzed under standardized condition to detect salivary elements zinc and copper. Concentrations of Zinc and copper were measured by using
... Show MoreBackground: habit is any purposeless action repeated unconsciously. It is a sign of lack of harmony between the subject and the surrounding environment. Deleterious oral habits such as finger sucking could be one of the etiological factors for altered oro-facial growth development. This study conducted to explore the association between finger sucking habit and malocclusion in deciduous dentition. Materials and method: Totally 40 chronic thumb sucker and 40 controls matching in age and gender were enrolled in the study. A study conducted by verifying different occlusal trait through the intra-oral examination. Thumb sucking habit diagnosed using data gathered from parents. Results: The statistical analysis showed a highly significant dif
... Show MoreReservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr
... Show MoreAn adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th
... Show MoreThis paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
... Show MoreThis work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
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... Show MoreThis paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
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