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Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that the
proposedmethod obtained very good results but it requires more testing on different types of Skin
Cancer Images.

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Publication Date
Sun Nov 01 2020
Journal Name
Iraqi Journal Of Laser
Rejuvenation of Facial Skin Using Fractional Er: YAG Laser
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Fractional Er: YAG laser resurfacing is increasingly used for treating rhytides and photo aged skin because of its favorable benefit‐risk ratio. The multi-stacking and variable pulse width technology opened a wide horizon of rejuvenation treatments using this type of laser. To evaluate the efficacy and safety of the use of fractional 2940 nm Er: YAG laser in facial skin rejuvenation. Twelve female patients with mean age 48.3 years and multiple degrees of aging signs and solar skin damages, were treated with 2 sessions, one month apart by fractional Er: YAG laser. Each session consisted of 2 steps, the first step employed the use of the multi stack ablative fractional mode and the fractional long pulsed non-ablative mode settings were u

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Negative skin friction evaluation and mitigation: A review study
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Publication Date
Fri Apr 01 2022
Journal Name
Neuroquantology
Optical Distinguish of Malignancy Cases of Skin Tumors Images
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The aim of the study is to detect the malignant conditions of the skin tumors through the features of optical images. This research included some of image processing techniques to detect skin cancer as a strong threat to human beings' lives. Using image processing and analysis methods to improves the ability of pathologists to detect this disease leading to more specified diagnosis and better treatment of them. One hundred images were collected from Benign and Malignant tumors and some appropriate image features were calculated, like Maximum Probability, Entropy, Coefficient of Variation, Homogeneity and Contrast, and using Minimum Distance method to separate these images. These features with Minimum Distance as a proposed making decision a

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Building marketing culture and reflection on the mental image Search for a pilot sample of managers in the General Company for Vegetable Oil Industry
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          The subject of marketing culture and mental image is one of the important topics in the field of management. There is no study that combines these two variables. The research is important because of the increasing importance of the subject. The future direction of the company in question will support the company's economic and marketing responsibilities. And reflect the company's mental image, as a culture that contributes to changing the reality of the organization investigated by polling the views of a sample of managers in the General Company for Vegetable Oil Industry, which (30) out of the (65) individual, and There are two hypotheses of research: There is a significant

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Publication Date
Thu Jul 29 2021
Journal Name
Arab Science Heritage Journal
صورة الانقلاب الديني في اسبانيا في العصور الوسطى
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The research entitled (Image of the Religious Coup in Spain in the Middle Ages) aims to shed light on the prevailing image of the religious coup in Spain during the Middle Aga

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Publication Date
Mon Sep 30 2024
Journal Name
Al-mustansiriyah Journal Of Science
A Transfer Learning Approach for Arabic Image Captions
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Publication Date
Sat Nov 02 2019
Journal Name
Advances In Intelligent Systems And Computing
Spin-Image Descriptors for Text-Independent Speaker Recognition
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Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Utilizing Deep Learning Technique for Arabic Image Captioning
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Publication Date
Fri Jul 01 2016
Journal Name
International Journal Of Computer Science And Mobile Computing
. Interpolative Absolute Block Truncation Coding for Image Compression
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Publication Date
Mon Apr 17 2023
Journal Name
Wireless Communications And Mobile Computing
A Double Clustering Approach for Color Image Segmentation
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

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