Preferred Language
Articles
/
zhiHlJUBVTCNdQwCuXxB
Deep Learning and Fusion Techniques for High-Precision Image Matting:
...Show More Authors

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k dataset demonstrate superior performance compared to traditional methods, achieving higher accuracy, faster processing speed, and improved boundary preservation. Novelty: The proposed model effectively combines deep learning with fusion techniques, enhancing matting quality while maintaining robustness across various environmental conditions. Implications: These findings highlight the potential of integrating fusion techniques with deep learning for image matting, offering valuable insights for future research in automated image processing applications, including augmented reality, gaming, and interactive video technologies. Highlights:   Better Precision: Fusion techniques enhance fine detail preservation. Faster Processing: Lightweight U-Net improves speed and accuracy. Wide Applications: Useful for AR, gaming, and video processing.   Keywords: Deep image matting, computer vision, deep learning, fusion techniques, U-Net

View Publication Preview PDF
Quick Preview PDF
Publication Date
Tue Jan 01 2019
Journal Name
Science International
USING CRYPTOANALYSIS POLICIES AND TECHNIQUES TO CREATE STRONG PASSWORD
...Show More Authors

Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
High performance work systems and general industrial enterprise performance
...Show More Authors

High performance work systems and general industrial enterprise performance

View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
Speech Emotion Recognition Using MELBP Variants of Spectrogram Image
...Show More Authors

View Publication Preview PDF
Scopus (10)
Crossref (5)
Scopus Crossref
Publication Date
Sun Sep 03 2023
Journal Name
Wireless Personal Communications
Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms
...Show More Authors

View Publication
Scopus (10)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
...Show More Authors

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (5)
Scopus Crossref
Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
...Show More Authors

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

... Show More
View Publication Preview PDF
Scopus (12)
Crossref (12)
Scopus Crossref
Publication Date
Wed May 31 2017
Journal Name
Journal Of Engineering
Evaluating the Performance of High Modulus Asphalt Concrete Mixture for Base Course in Iraq
...Show More Authors

In the 1980s, the French Administration Roads LCPC developed high modulus mixtures (EME) by using hard binder. This type of mixture presented good resistance to moisture damage and improved mechanical properties for asphalt mixtures including high modulus, good fatigue behaviour and excellent resistance to rutting. In Iraq, this type of mixture has not been used yet. The main objective of this research is to evaluate the performance of high modulus mixtures and comparing them with the conventional mixture, to achieve this objective, asphalt concrete mixes were prepared and then tested to evaluate their engineering properties which include moisture damage, resilient modulus, permanent deformation and fatigue characteristics. These pro

... Show More
Publication Date
Sat Sep 21 2013
Journal Name
Nonlinear Dynamics
BER performance enhancement for secure wireless optical communication systems based on chaotic MIMO techniques
...Show More Authors

View Publication
Scopus (7)
Crossref (7)
Scopus Clarivate Crossref
Publication Date
Sat Jul 09 2022
Journal Name
Optik
The role of Ag NPs in PVA electrospun NFs for ultra-high sensitivity photodetector
...Show More Authors

This work aimed to produce PVA and PVA/Ag nanofibers ultra-high sensitivity photodetector by electrospinning. The electrospinning process was used to successfully prepare PVA nanofibers and a PVA-Ag nanofiber composite. FE-SEM, XRD, UV, I-V characterizations are used to study the morphological, structural, optical, and electrical properties of the material. In contrast, the PVA-Ag nanofiber composite film displayed a cubic structure with favored orientation (200) that indicated the presence of Ag NPs in the PVA-Ag nanofibers film. While the optical energy gap for PVA was 3.96 eV, it was only 2.14 eV for PVA-Ag nanofibers composite film, making this composite sensitive to visible light, particularly green light at 550 nm with a 65% photosens

... Show More
Scopus (7)
Scopus
Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Darwinian Philosophy as Optimization Method for Design High Reflection Mirror Include New Merit Function
...Show More Authors

In this paper we proposes the philosophy of the Darwinian selection as synthesis method called Genetic algorithm ( GA ), and include new merit function with simple form then its uses in other works for designing one of the kinds of multilayer optical filters called high reflection mirror. Here we intend to investigate solutions for many practical problems. This work appears designed high reflection mirror that have good performance with reduction the number of layers, which can enable one to controlling the errors effect of the thickness layers on the final product, where in this work we can yield such a solution in a very shorter time by controlling the length of the chromosome and optimal genetic operators . Res

... Show More
View Publication Preview PDF
Crossref