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3D scenes semantic segmentation using deep learning based Survey
Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the power and popular tool for data and image processing in computer vision, used for many applications like “image recognition”, “object detection”, “semantic segmentation”, In this research paper, provide survey a background for many techniques designed to 3 Dimensions point cloud semantic segmentation in different domains on many several available free datasets and also making a comparison between these methods.</p>
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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Surface Shape Descriptors on 3D Faces

The general objective of surface shape descriptors techniques is to categorize several surface shapes from collection data. Gaussian (K) and Mean (H) curvatures are the most broadly utilized indicators for surface shape characterization in collection image analysis. This paper explains the details of some descriptions (K and H), The discriminating power of 3D descriptors taken away from 3D surfaces (faces) is analyzed and present the experiment results of applying these descriptions on 3D face (with polygon mesh and point cloud representations). The results shows that Gaussian and Mean curvatures are important to discover unique points on the 3d surface (face) and the experiment result shows that these curvatures are very useful for some

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Energy Consumption Prediction of Smart Buildings by Using Machine Learning Techniques

     This paper presents an IoT smart building platform with fog and cloud computing capable of performing near real-time predictive analytics in fog nodes. The researchers explained thoroughly the internet of things in smart buildings, the big data analytics, and the fog and cloud computing technologies. They then presented the smart platform, its requirements, and its components. The datasets on which the analytics will be run will be displayed. The linear regression and the support vector regression data mining techniques are presented. Those two machine learning models are implemented with the appropriate techniques, starting by cleaning and preparing the data visualization and uncovering hidden information about the behavior of

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
SMS Spam Detection Using Multiple Linear Regression and Extreme Learning Machines

     With the growth of the use mobile phones, people have become increasingly interested in using Short Message Services (SMS) as the most suitable communications service. The popularity of SMS has also given rise to SMS spam, which refers to any unwanted message sent to a mobile phone as a text. Spam may cause many problems, such as traffic bottlenecks or stealing important users' information. This paper,  presents a new model that extracts seven features from each message before applying a Multiple Linear Regression (MLR) to assign a weight to each of the extracted features. The message features are fed into the Extreme Learning Machine (ELM) to determine whether they are spam or ham. To evaluate the proposed model, the UCI bench

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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
Implementable Self-Learning PID Controller Using Least Mean Square Adaptive Algorithm

More than 95% of the industrial controllers in use today are PID or modified PID controllers. However, the PID is manually tuning to be responsive so that the Process Variable is rapidly and steady moved to track the set point with minimize overshoot and stable output. The paper presents generic teal-time PID controller architecture. The developed architecture is based on the adaption of each of the three controller parameters (PID) to be self- learning using individual least mean square algorithm (LMS). The adaptive PID is verified and compared with the classical PID. The rapid realization of the adaptive PID architecture allows the readily fabrication into a hardware version either ASIC or reconfigurable.

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches

Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Structural Interpretations for Zubair Formation in Kumait oil field, Using 3D Seismic Reflection Data, Southern-East Iraq

     This study deals with the interpretation of structural 3D seismic reflection of the Kumait oil field in southern Iraq within the administrative boundaries of the Maysan Governorate. Synthetic seismograms are prepared by using available data of the Kt-1 oil field by using Petrel software to define and pick the reflector on the seismic section of the Zubair Formation, Which represents the Cretaceous Age. The study shows that the Kumait structure is an anticline fold. It is thought to be a structure trap caused by the collision of the Arabian and Iranian plates and trending in the same direction as driving factors in the area, which are from the northwest to the southeast, and the overall trend of strata is north and northeast. Sei

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Publication Date
Wed Jul 01 2015
Journal Name
Magnetic Resonance Imaging
Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Detection of Shallow Cavities Using 3D Resistivity Technique in a Small Site Near Haditha City, Western Iraq

     Iraqi western desert is characterized by a widespread karst phenomenon and caves. Euphrates formation (Lower Miocene) includes enormous sinkholes and cavities within carbonate rocks that usually cause severe damages to any kind of engineering facilities built over it. 3D resistivity imaging techniques were used in detecting this kind of cavities in complicated lithology. The 3D view was fulfilled by collating seven 2D imaging lines. The 2D imaging survey was carried out by Dipole-dipole array with (n) factor and electrode spacing (a) of 6 and 2m respectively. The horizontal slices of the 3D models give a good subsurface picture. There are many caves in all directions (x, y, z). They reveal many small caves near the surface. Thes

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
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Publication Date
Wed Apr 28 2021
Journal Name
Misan Journal For Physical Education Sciences
The Effectiveness of Using Generative Learning Model in Learning Kinetic Series on Rings and Horizontal Bar In Artistic Gymnastics for men

The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di

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