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bsj-3009
Reconstruction of Three-Dimensional Object from Two-Dimensional Images by Utilizing Distance Regularized Level Algorithm and Mesh Object Generation
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Three-dimensional (3D) reconstruction from images is a most beneficial method of object regeneration by using a photo-realistic way that can be used in many fields. For industrial fields, it can be used to visualize the cracks within alloys or walls. In medical fields, it has been used as 3D scanner to reconstruct some human organs such as internal nose for plastic surgery or to reconstruct ear canal for fabricating a hearing aid device, and others. These applications need high accuracy details and measurement that represent the main issue which should be taken in consideration, also the other issues are cost, movability, and ease of use which should be taken into consideration. This work has presented an approach for design and constructed a low-cost three-dimensional object scanner. We have proposed a 3D canal reconstruction system (ear or nose) based on using 2D images for reconstruction 3D object. A low-cost EndoScope with a proposed program based upon utilized the segmentation algorithm type “Distance Regularized Level” to segment active edges from images then generate mesh object in order to generate 3D structure for small canals or cracks. The results show good accuracy of the reconstructed object in both details and their measurements which are related to the success in the reconstruction of algorithm that yields good three-dimensional meshes object.

 

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Publication Date
Mon Oct 01 2012
Journal Name
Computers & Mathematics With Applications
Boundary element formulations for the numerical solution of two-dimensional diffusion problems with variable coefficients
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Publication Date
Mon Oct 01 2018
Journal Name
2018 International Conference On Advanced Science And Engineering (icoase)
Real-Time Face Tracking and Recognition System Using Kanade-Lucas-Tomasi and Two-Dimensional Principal Component Analysis
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Fri Dec 01 2017
Journal Name
British Journal Of Oral And Maxillofacial Surgery
A novel approach for the three-dimensional evaluation of facial asymmetry of unilateral cleft lip and palate patients (UCLP)
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Publication Date
Thu Sep 01 2022
Journal Name
Precision Radiation Oncology
Assessment of dose‐volume histogram statistics using three‐dimensional conformal techniques in breast cancer adjuvant radiotherapy treatment
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Abstract<sec><title>Objective

Breast cancer (BC) is first of the top 10 malignancies in Iraq. Dose‐volume histograms (DVHs) are most commonly used as a plan evaluation tool. This study aimed to assess DVH statistics using three‐dimensional conformal radiotherapies in BC in an adjuvant setting.

Methods

A retrospective study of 70 histologically confirmed women diagnosed with BC was reviewed. The study was conducted between November 2020 and May 2021, planning for treatment with adjuvant three‐dimensional conformal radiotherapies. The treatment plan used for each woman was based on an analysis of the volumetric dose, inclu

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Effects of Castor Oil Nanoemulsion Extracted by Hexane on the Fourth Larval stage of Culex quinquefsciatus from Al Hawizeh Marsh/Iraq, and Non- Targeted Organism
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           The current study aims to show the importance of plant products as mosquitocides against Culex quinquefasciatus. Castor oil Nanoemulsions were subedit in various ratios including castor oil, ethanol, tween 80, and deionized water by using ultrasonication. Thermodynamic, centrifugation, PH, assay which improved that the formula  of 10 ml  of castor  oil, ethanol  5ml, tween 80 (14 ml) and deionized water 71ml was more stable than other formulas. The stable formula of castor oil nanoemulsion was characterized by transmission electron microscopy (TEM) and dynamic light scattering (DLS). Nanoemulsion droplets were spherical in shape and were found to have a Z-average diameter of 87.4nm. A concentration of ca

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Publication Date
Mon Mar 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Bionics-Based Approach for Object Tracking to Implement in Robot Applications
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In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Wed Dec 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
Online medical consultation: covid-19 system using software object-oriented approach
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The internet has been a source of medical information, it has been used for online medical consultation (OMC). OMC is now offered by many providers internationally with diverse models and features. In OMC, consultations and treatments are available 24/7. The covid-19 pandemic across-the-board, many people unable to go to hospital or clinic because the spread of the virus. This paper tried to answer two research questions. The first one on how the OMC can help the patients during covid-19 pandemic. A literature review was conducted to answer the first research question. The second one on how to develop system in OMC related to covid-19 pandemic. The system was developed by Visual Studio 2019 using software object-oriented approach. O

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Publication Date
Thu Oct 03 2024
Journal Name
Retos
The effect of purposeful three-dimensional training on developing some motor abilities and skill performance among female fencing players
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O estudo destaca a necessidade crítica de se focar nas capacidades físicas, motoras e técnicas das jogadoras de esgrima, desenvolvendo e testando metodologias de treino modernas, baseadas na ciência, adaptadas às exigências específicas do desporto. O objetivo do estudo foi avaliar a eficácia do treino tridimensional visando melhorar as capacidades motoras e o desempenho técnico dos participantes. Recorrendo a um desenho experimental, o estudo envolveu a formação de grupos experimentais e de controlo. A amostra incluiu 16 esgrimistas da Faculdade Feminina de Educação Física e Ciências do Desporto. Após a exclusão de dois jogadores durante a fase exploratória, os restantes 14 foram divididos igualmente em grupos experimental

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