Khalid M. Amin

اختيار الموقع	تسجيل دخول

An Efficient System for Melanoma Diagnosis in Dermoscopic Images
Ahmed Afifi - جامعة المنوفية - كلية الحاسبات والمعلومات
Khalid M. Amin - جامعة المنوفية - كلية الحاسبات والمعلومات

الكلمات الدالة recursive feature elimination algorithm,
random forests classifier,
classes imbalance problem,
clinical situations,
neighborhood cleaning rule,
borderline synthetic minority over-sampling,
extra tree classifier,
Melanoma diagnosis,
dermoscopic images …

تم النشر في : IEEE
تم النشر بتاريخ : 01/02/2018
الملحقات : 19.doc

تحميل

The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt /
Khalid M. Amin - المجلس الاعلى للجامعات
Mostafa A. Ahmad - المجلس الاعلى للجامعات
A. Ali - المجلس الاعلى للجامعات

الكلمات الدالة Document Image Processing, Binarization, Evaluation, wavelet de-noising.
الصفحات 271 - 282 p.
تم النشر بتاريخ : 01/01/2015

A novel breast tumor classification algorithm using neutrosophic score features /
Khalid M. Amin - جامعة المنوفية - كلية الحاسبات والمعلومات
A.I. Shahin - EGYPT
Yanhui Guo - USA

الكلمات الدالة A lot of studies confirmed the seriousness of breast cancer as the most tumors lethal to
women worldwide. Early detection and diagnosis of breast cancer are of great importance
to increase treatment options and patients’ survival rate. Ultrasound is one of the most frequently
used methods to detect and diagnosis breast tumor due to its harmlessness and
inexpensiveness. However, problems were found in the tumor diagnosis and classification
as benign and malign on ultrasound image for its vagueness, such as speckle noise and low
contrast. In this paper, we propose a novel breast tumor classification algorithm that combines
texture and morphologic features based on neutrosophic similarity score. Then, a
supervised feature selection technique is employed to reduce feature space. Finally, a support
vector machine (SVM) classifier is employed to prove the discrimination power of the
proposed features set. The proposed system is validated by 112 cases (58 malign, 54
benign). The experimental results show that such features set is promising and 99.1%
classification accuracy is achieved.
الصفحات 210 - 220 P.
تم النشر في : Elsevier
تم النشر بتاريخ : 01/01/2016
الملحقات : 1 - Copy.docx

تحميل

A novel breast tumor classification algorithm using neutrosophic score features /
Khalid M. Amin - جامعة المنوفية - كلية الحاسبات والمعلومات
A.I. Shahin - جامعة القاهرة
Yanhui Guo -

الكلمات الدالة Breast cancer
Ultrasound images
Feature extraction
Neutrosophic similarity score.
الصفحات 210–220 p.
تم النشر في : Elsevier
تم النشر بتاريخ : 01/03/2016
الملحقات : 1 - Copy.docx

تحميل

Static video summarization approach using Binary Robust Invariant Scalable Keypoints
Eman Morad - جامعة المنوفية - كلية الحاسبات والمعلومات
Khalid M. Amin - جامعة المنوفية - كلية الحاسبات والمعلومات
Sameh Zarif - جامعة المنوفية - كلية الحاسبات والمعلومات

الكلمات الدالة Video summarization, shot boundary detection, keyframe extraction, Binary Robust Invariant Scalable Keypoints (BRISK).
الصفحات 1-6
الملحقات : 7.pdf

تحميل