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Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CNN infrastructure. Findings: The results acquired through the investigated CBIR system alongside the benchmarked results have clearly indicated that the suggested technique had the best performance with the overall accuracy at 88.29% as opposed to the other sets of data adopted in the experiments. The outstanding results indicate clearly that the suggested method was effective for all the sets of data. Improvements/Applications: As a result of this study, it was found the revealed that the multiple image representation was redundant for extraction accuracy, and the findings from the study indicated that automatically retrieved features are capable and reliable in generating accurate outcomes.

Publication Date
Thu Oct 01 2009
Journal Name
Iraqi Journal Of Physics
Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model Histogram linear Contrast Stretching (MMHLCS) method

Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
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Publication Date
Fri Jan 01 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Publication Date
Thu Dec 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering
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Publication Date
Mon Dec 18 2023
Journal Name
Journal Of Iraqi Al-khwarizmi
Fibrewise Multi-Compact and Locally Multi- Compact Spaces

The primary objective of this paper is to introduce a new concept of fibrewise topological spaces on D is named fibrewise multi- topological spaces on D. Also, we entroduce the concepts of multi-proper, fibrewise multi-compact, fibrewise locally multi-compact spaces, Moreover, we study relationships between fibrewise multi-compact (resp., locally multi-compac) space and some fibrewise multi-separation axioms.

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Publication Date
Sat Jun 03 2023
Journal Name
Iraqi Journal Of Science
Determination of hydroquinone in pure form and pharmaceutical preparations using Batch and FIA-Merging Zone techniques with spectrophotometric detection

In this study, a new, rapid and sensitive batch and flow injection-merging zones spectrophotometric methods for the determination of hydroquinone in a pure material and in pharmaceutical preparation were proposed. These methods were based on the oxidative-coupling reaction of HQ with 2,4-dinitrophenylhydazine (DNPH) in the presence of sodium periodate and sodium hydroxide to form a dark brown water slouble dye that is stable and has maximum absorption at 530 nm, graphs of absorbance versus concentration show that Beer's low is obeyed over the concentration rang of 1-40 and 3-300 μg.ml-1 of hydroquinone, with detection limits of 0.162 and 0.510 μg.ml-1 of hydroquinone for batch and FIA methods, respectively. The optimized FIA system is

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Publication Date
Wed Dec 08 2021
Journal Name
J. Inf. Hiding Multim. Signal Process.
Predication of Most Significant Features in Medical Image by Utilized CNN and Heatmap.

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Publication Date
Wed Oct 18 2023
Journal Name
Ieee Access
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Publication Date
Fri Sep 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Document retrieval using term term frequency inverse sentence frequency weighting scheme

The need for an efficient method to find the furthermost appropriate document corresponding to a particular search query has become crucial due to the exponential development in the number of papers that are now readily available to us on the web. The vector space model (VSM) a perfect model used in “information retrieval”, represents these words as a vector in space and gives them weights via a popular weighting method known as term frequency inverse document frequency (TF-IDF). In this research, work has been proposed to retrieve the most relevant document focused on representing documents and queries as vectors comprising average term term frequency inverse sentence frequency (TF-ISF) weights instead of representing them as v

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Publication Date
Tue Dec 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Cloud Manufacturing framework for controlling and monitoring of machines

Due to the development that occurs in the technologies of information system many techniques was introduced and played important role in the connection between machines and peoples through internet, also it used to control and monitor of machines, these technologies called cloud computing and Internet of Things. With the replacement of computing resources with manufacturing resources cloud computing named converted into cloud manufacturing.

In this research cloud computing was used in the field of manufacturing to automate the process of selecting G-Code that Computer Numerical Control machine work it, this process was applied by the using of this machine with Radio Frequency Identification and a AWS Cloud services and some of py

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