Audio-visual detection and recognition system is thought to become the most promising methods for many applications includes surveillance, speech recognition, eavesdropping devices, intelligence operations, etc. In the recent field of human recognition, the majority of the research be- coming performed presently is focused on the reidentification of various body images taken by several cameras or its focuses on recognized audio-only. However, in some cases these traditional methods can- not be useful when used alone such as in indoor surveillance systems, that are installed close to the ceiling and capture images right from above in a downwards direction and in some cases people don't look straight the cameras or it cannot be added in some area such as W.C. or sleeping room. Thus, its commonly difficult to identify any movement or breakthrough process, on the other hand when need to pursue suspect when enter a building or party to identify his location and/or listen to his speech only and isolate it from other voices or noises, the other. Hence, the use of the hybrid combination technique is very effective. In this work, we proposed a multimodal human recognition approach that utilizes both the face and audio and is based upon a deep convolutional neural network (CNN). Mainly, to solve the challenge of not capturing part of the body, final results of recognizing via separate CNNs of VGG Face16 and ResNet50 are joined together depending on the score-level combination by Weighted Sum rule to enhance recognition performance. The results show that the proposed system success to recognise each person from his voice and/or his face captured. In addition, the system can separate the person voice and isolate it from noisy environment and determine the existence of desired person.
In this study three reactive dyes (blue B, red R and yellow Y) in single , binary and ternary solution were adsorbed by activated carbon AC in equilibrium and kinetic experiments. Surface area, Bulk and real density, and porosity were carried out for the activated carbon.
Batch Experiments of pH (2.5-8.5) and initial concentration (5-100) mg/l were carried out for single solution for each dye. Experiments of adsorbent dosage effect (0.1-1)g per 100 ml were studied as a variable to evaluate uptake% and adsorption capacity for single dyes(5, 10) ppm, binary and ternary (10) ppm of mixture solutions solution of dyes. Langmuir, and Freundlich, models were used as Equilibrium isotherm models for single solution. Extended Langmuir and Freun
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One of the most important techniques for preparing nanoparticle material is Pulsed Laser Ablation in Liquid technique (PLAL). Carbon nanoparticles were prepared using PLAL, and the carbon target was immersed in Ultrapure water (UPW) then irradiated with Q-switched Nd:YAG laser (1064 nm) and six ns pulse duration. In this process, an Nd:YAG laser beam was focused near the carbon surface. Nanoparticles synthesized using laser irradiation were studied by observing the effects of varying incident laser pulse intensities (250, 500, 750, 1000) mJ on the particle size (20.52, 36.97, 48.72, and 61.53) nm, respectively. In addition, nanoparticles were characterized by means of the Atomic Force Microscopy (AFM) test, pH easurement
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The aim of this study is to investigate the ability of malachite green (MG) combined with 650nm diode laser to kill Candida albicans and to spectrally study the MG photodegradation after photodynamic therapy (PDT) spectrally. Cultures of Candida albicans were exposed to 40mW, 650 nm diode laser in the absence of MG. In PDT group, the MG was added to the Candida suspension for 5 min then exposed to diode laser for (5, 10, 15, 20) min at power density of 0.59W/cm2. The absorption spectrum of the photosensitized fungal suspension was obtained. The data were submitted to T-test (p<0.05). A 650nm diode laser in the presence of MG reduced the number of CFU/ml in 98.4%. Laser with 650nm alone and MG alone did not reduce significantly the num
... Show MoreThere are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja
Image segmentation can be defined as a cutting or segmenting process of the digital image into many useful points which are called segmentation, that includes image elements contribute with certain attributes different form Pixel that constitute other parts. Two phases were followed in image processing by the researcher in this paper. At the beginning, pre-processing image on images was made before the segmentation process through statistical confidence intervals that can be used for estimate of unknown remarks suggested by Acho & Buenestado in 2018. Then, the second phase includes image segmentation process by using "Bernsen's Thresholding Technique" in the first phase. The researcher drew a conclusion that in case of utilizing
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AG Al-Ghazzi, 2009