Ahmed Elaraby
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View article: Quantum Edge Detection in Digital Imaging: A Novel Approach Using Quantum Exponential Entropy
Quantum Edge Detection in Digital Imaging: A Novel Approach Using Quantum Exponential Entropy Open
View article: Advancing Lymphoma Diagnosis in Histopathology Image Classification Using Multi Deep Learning Models
Advancing Lymphoma Diagnosis in Histopathology Image Classification Using Multi Deep Learning Models Open
View article: An Automated Contrast Enhancement Approach for Aerial Images
An Automated Contrast Enhancement Approach for Aerial Images Open
View article: A Novel Hybrid Algorithm for Fake News Detection
A Novel Hybrid Algorithm for Fake News Detection Open
The proliferation of erroneous information on social media has a deleterious effect on both people and society. In order to mitigate the drawbacks of social media, it is crucial to distinguish between authentic and misleading information. …
View article: Wireless body area network: Architecture and security mechanism for healthcare using internet of things
Wireless body area network: Architecture and security mechanism for healthcare using internet of things Open
Internet of Things (IoT) enabled wireless body area network (WBAN) is a novel technology that combines medical, wireless, and non-medical devices for healthcare management applications. Indoor healthcare institutions, such as hospitals, ma…
View article: Hybrid CNN-GRU Model for Real-Time Blood Glucose Forecasting: Enhancing IoT-Based Diabetes Management with AI
Hybrid CNN-GRU Model for Real-Time Blood Glucose Forecasting: Enhancing IoT-Based Diabetes Management with AI Open
For people with diabetes, controlling blood glucose level (BGL) is a significant issue since the disease affects how the body metabolizes food, which makes careful insulin regulation necessary. Patients have to manually check their blood s…
View article: An approach for classification of breast cancer using lightweight deep convolution neural network
An approach for classification of breast cancer using lightweight deep convolution neural network Open
The rapid advancement of deep learning has generated considerable enthusiasm regarding its utilization in addressing medical imaging issues. Machine learning (ML) methods can help radiologists to diagnose breast cancer (BCs) barring invasi…
View article: ArabBert-LSTM: improving Arabic sentiment analysis based on transformer model and Long Short-Term Memory
ArabBert-LSTM: improving Arabic sentiment analysis based on transformer model and Long Short-Term Memory Open
Sentiment analysis also referred to as opinion mining, plays a significant role in automating the identification of negative, positive, or neutral sentiments expressed in textual data. The proliferation of social networks, review sites, an…
View article: Designing of an effective e-learning website using inter-valued fuzzy hybrid MCDM concept: A pedagogical approach
Designing of an effective e-learning website using inter-valued fuzzy hybrid MCDM concept: A pedagogical approach Open
The demand for effective e-learning platforms requires prioritizing pedagogical excellence in online educational websites. Current approaches struggle with uncertainties, hindering optimal e-learning environments due to a lack of comprehen…
View article: Deep Learning-Based Classification of Melanoma and Non-Melanoma Skin Cancer
Deep Learning-Based Classification of Melanoma and Non-Melanoma Skin Cancer Open
Melanoma skin cancer is primarily characterized by poor prognostic responses.Surgical treatment can achieve advanced cure rate with early melanoma detection.Manual segmentation of suspected lesions aids early melanoma diagnosis.However, th…
View article: Rapid Grapevine Health Diagnosis Based on Digital Imaging and Deep Learning
Rapid Grapevine Health Diagnosis Based on Digital Imaging and Deep Learning Open
Deep learning plays a vital role in precise grapevine disease detection, yet practical applications for farmer assistance are scarce despite promising results. The objective of this research is to develop an intelligent approach, supported…
View article: Optimal Tree Depth in Decision Tree Classifiers for Predicting Heart Failure Mortality
Optimal Tree Depth in Decision Tree Classifiers for Predicting Heart Failure Mortality Open
The depth of a decision tree (DT) affects the performance of a DT classifier in predicting mortality caused by heart failure (HF). A deeper tree learns complex patterns within the data, theoretically leading to better predictive performanc…
View article: Digging for gold: evaluating the authenticity of saffron (Crocus sativus L.) via deep learning optimization
Digging for gold: evaluating the authenticity of saffron (Crocus sativus L.) via deep learning optimization Open
Introduction Saffron is one of the most coveted and one of the most tainted products in the global food market. A major challenge for the saffron industry is the difficulty to distinguish between adulterated and authentic dried saffron alo…
View article: An Optimized Deep Learning Approach for Robust Image Quality Classification
An Optimized Deep Learning Approach for Robust Image Quality Classification Open
This study presents a novel methodology for robust classification of image quality, a critical task in the domain of computer vision.The ability to accurately and promptly classify an image as being of inferior quality, due to factors such…
View article: Analyzing the Critical Parameters for Implementing Sustainable AI Cloud System in an IT Industry Using AHP-ISM-MICMAC Integrated Hybrid MCDM Model
Analyzing the Critical Parameters for Implementing Sustainable AI Cloud System in an IT Industry Using AHP-ISM-MICMAC Integrated Hybrid MCDM Model Open
This study aims to identify the critical parameters for implementing a sustainable artificial intelligence (AI) cloud system in the information technology industry (IT). To achieve this, an AHP-ISM-MICMAC integrated hybrid multi-criteria d…
View article: A Novel Deep Learning Approach for Brain Tumors Classification Using MRI Images
A Novel Deep Learning Approach for Brain Tumors Classification Using MRI Images Open
Early detection of brain tumors (BTs) can save valuable lives.BTs classification is usually accomplished by using magnetic resonance imaging (MRI), which is commonly carried out earlier than definitive talent surgery.Machine learning (ML) …
View article: Diabetic Retinopathy and Diabetic Macular Edema Detection Using Ensemble Based Convolutional Neural Networks
Diabetic Retinopathy and Diabetic Macular Edema Detection Using Ensemble Based Convolutional Neural Networks Open
Diabetic retinopathy (DR) and diabetic macular edema (DME) are forms of eye illness caused by diabetes that affects the blood vessels in the eyes, with the ground occupied by lesions of varied extent determining the disease burden. This is…
View article: Segmentation of Spectral Plant Images Using Generative Adversary Network Techniques
Segmentation of Spectral Plant Images Using Generative Adversary Network Techniques Open
The spectral image analysis of complex analytic systems is usually performed in analytical chemistry. Signals associated with the key analytics present in an image scene are extracted during spectral image analysis. Accordingly, the first …
View article: Quantum medical images processing foundations and applications
Quantum medical images processing foundations and applications Open
Medical imaging is considered one of the most important areas within scientific imaging due to the rapid and ongoing development in computer‐aided medical image visualisation, advances in analysis approaches, and computer‐aided diagnosis. …
View article: Classification of Bird Sound Using High-and Low-Complexity Convolutional Neural Networks
Classification of Bird Sound Using High-and Low-Complexity Convolutional Neural Networks Open
Birds are a reflection of environmental health as pollution and climate change affect biodiversity.Experts in ecology and machine learning stand to benefit the most from largescale monitoring of biodiversity.Today, convolutional neural net…
View article: Classification of Citrus Diseases Using Optimization Deep Learning Approach
Classification of Citrus Diseases Using Optimization Deep Learning Approach Open
Most plant diseases have apparent signs, and today’s recognized method is for an expert plant pathologist to identify the disease by looking at infected plant leaves using a microscope. The fact is that manually diagnosing diseases is time…
View article: An approach for cross-modality guided quality enhancement of liver image
An approach for cross-modality guided quality enhancement of liver image Open
A novel approach for multimodal liver image contrast enhancement is put forward in this paper. The proposed approach utilizes magnetic resonance imaging (MRI) scan of liver as a guide to enhance the structures of computed tomography …
View article: Classification COVID-19 Based on Enhancement X-Ray Images and Low Complexity Model
Classification COVID-19 Based on Enhancement X-Ray Images and Low Complexity Model Open
COVID-19 has been considered one of the recent epidemics that occurred at the last of 2019 and the beginning of 2020 that world widespread. This spread of COVID-19 requires a fast technique for diagnosis to make the appropriate decision fo…
View article: Generalized Exponential Fuzzy Entropy Approach for Automatic Segmentation of Chest CT with COVID‐19 Infection
Generalized Exponential Fuzzy Entropy Approach for Automatic Segmentation of Chest CT with COVID‐19 Infection Open
The proposed work describes an approach for the segmentation of abnormal lung CT scans of COVID‐19. Lung diseases are the leading killer in both men and women. The pulmonary experts normally make attempts, such as early detection of patien…
View article: Segmentation of Activated Sludge Flocs in Microscopic Images for Monitoring Wastewater Treatment
Segmentation of Activated Sludge Flocs in Microscopic Images for Monitoring Wastewater Treatment Open
The proposed work describes an approach for segmentation of activated sludge flocs from the microscopic images for monitoring wastewater treatment. The morphological features of flocs (microbial aggregates) and filaments are related to the…
View article: Multi-Phase Information Theory-Based Algorithm for Edge Detection of Aerial Images
Multi-Phase Information Theory-Based Algorithm for Edge Detection of Aerial Images Open
Edge detection is the diverse way used to detect boundaries in digital images. Many methods exist to achieve this purpose, yet not all of them can produce results with high detection ratios. Some may have high complexity, and others may re…
View article: A Framework for Cross-Modality Guided Contrast Enhancement of CT Liver Using MRI
A Framework for Cross-Modality Guided Contrast Enhancement of CT Liver Using MRI Open
In liver medical imaging, physicians always detect, monitor, and characterize liver diseases by visually assessing of liver medical images. Computed Tomographic (CT) imaging is considered as one of the efficient medical imaging modalities …
View article: DEEP LEARNING APPLICATION FOR IMAGE ENHANCEMENT
DEEP LEARNING APPLICATION FOR IMAGE ENHANCEMENT Open
Recently, deep learning has obtained a central position toward our daily life automation and deliveredconsiderable improvements as compared to traditional algorithms of machine learning. Enhancing ofimage quality is a fundamental image pro…
View article: Optimization of Deep Learning Model for Plant Disease Detection Using Particle Swarm Optimizer
Optimization of Deep Learning Model for Plant Disease Detection Using Particle Swarm Optimizer Open
Plant diseases are a major impendence to food security, and due to a lack of key infrastructure in many regions of the world, quick identification is still challenging. Harvest losses owing to illnesses are a severe problem for both large …
View article: Comparison of Segmentation Performance of Activated Sludge Flocs Using Bright-Field and Phase-Contrast Microscopy at Different Magnifications
Comparison of Segmentation Performance of Activated Sludge Flocs Using Bright-Field and Phase-Contrast Microscopy at Different Magnifications Open
Activated sludge (AS) is a type of process which is commonly used for the treatment of sewage and industrial wastewater. In this treatment process, the settling of the sludge flocs is important to ensure the normal functioning of the syste…