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

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

Fiber optics technology has shown immense applications in the areas of medicine, telecommunication, and imaging. For these particular applications, it requires fibers with precise cleaving. In this paper, we will demonstrate a quick, simple and efficient cleaving method that can result in a high-quality fiber surface that works well for many fiber-optic applications. The smooth tip and good surface quality obtained on the cleaved surface of optical fiber is demonstrated by using a microscope imaging system and was flat surface with a 900 angle for perpendicular cleavages. The precision cleaver provides smooth and high-quality cleaves on single-fiber surfaces as opposed to the ruby scribe pen. The defects that may occur during the cleaving p

The environment contemporary works for the insurance companies have seen a number of technological developments and changes rapidly in light of the intense competition in the insurance market, and this affects human behavior in the workplace, and to director in his work needs to be a set of managerial skills. so we find compensation activity in companies insurance needs a high managerial skills, so that compensation, director of the settlement procedure successfully. So research aims to test two hypotheses two major belongings variables search using some statistical methods to extract the results and interpretation and analysis (such as arithmetic mean, standard deviation, percentages, Alpha Cronbach's coefficient, Pearson correlation co

Deep Learning Techniques For Skull Stripping of Brain MR Images