M.I. Dessouky

Menoufia University · Department of Electronics and Communication Engineering

As the demand for high-bandwidth Internet connections continues to surge, industries are exploring innovative ways to harness this connectivity, and smart agriculture stands at the forefront of this evolution. In this paper, we delve into the challenges faced by Internet Service Providers (ISPs) in efficiently managing bandwidth and traffic within...

Super-Resolution (SR) reconstruction of images has an extreme importance for vision applications. Numerous algorithms have been introduced for this purpose in recent years. This paper presents a cost-effective approach for visual quality and resolution enhancement of 3D Video (3DV) sequences. The basic idea of this approach is to employ a deep lear...

The phrase "anomaly detection" is often used to describe any technique that looks for samples that differ from expected patterns. Depending on availability of data labels, types of abnormalities and applications, many anomaly detection techniques have been developed. This study aims to give a well-organized and a thorough review of anomaly detectio...

Biometric systems have recently become popular for modern security applications. Unfortunately, these systems have been the target of many hacking attempts. Biometrics in biometric databases will be lost forever if they are hacked and stolen. As a result, there is an urgent need to implement modern upgradable biometric systems. Cancelable biometric...

A key function of wireless sensor networks (WSN) is data collection. Due to the hot spot issue and the limited energy supply, developing data gathering techniques is complicated. The WSN faces three main challenges: security, data routing, and processing a lot of data. Since compressive sensing can achieve simultaneous sampling and compression, it...

Audio steganography is a tool for concealing data (a secret message) inside an audio signal (a carrier). It is regarded as an essential approach for information security. This paper presents a proposed technique for audio signal steganography, which is implemented in the wavelet domain, with a preprocessing enhancement step. First, adaptive Wiener...

This paper presents a simplified fractal image compression algorithm, which is implemented on a block-by-block basis. This algorithm achieves a Compression Ratio (CR) of up to 10 with a Peak Signal-to-Noise Ratio (PSNR) as high as 35 dB. Hence, it is very appropriate for the new applications of underwater communication. The idea of the proposed alg...

In the modern landscape, robust data communication is pivotal for businesses and lifestyles. This has led to intricate demands from enterprise customers for sophisticated communication solutions. As a response, MPLS (Multiprotocol Label Switching) technology is being leveraged to meet these complex connectivity needs. This paper undertakes a compre...

This paper is concerned with the issue of brain tumor segmentation and detection. Three types of segmentation algorithms are considered on Magnetic Resonance (MR) images: watershed, threshold and hybrid segmentation. In addition, a new strategy for detection prior to segmentation is adopted. The objective of this strategy is to reduce the dimension...

This paper presents two efficient frameworks for seizure detection and prediction that depend on statistical analysis. The common thread between them is the selection of certain attributes extracted from the electroencephalography (EEG) signals and the derivation of probability density functions (PDFs) of these attributes in two different types of...

Regularized signal and image reconstruction is one of the powerful tools to acquire original signals or images from the versions degraded with convolution and noise effects. The main problem encountered in regularized reconstruction of images is the estimation of the regularization parameter, as the quality and fidelity of the reconstructed images...

Regularized signal and image reconstruction is one of the powerful tools to acquire original signals or images from the versions degraded with convolution and noise effects. The main problem encountered in regularized reconstruction of images is the estimation of the regularization parameter, as the quality and fidelity of the reconstructed images...

Brain tumor is an abnormal cell population that occurs in the brain. Currently, medical imaging techniques play a vital role in brain tumor diagnosis and classification. Brain tumor classification based on Magnetic Resonance Imaging (MRI) has become a promising research area in the field of medical imaging systems. In the brain image, the size of t...

Automatic modulation classification (AMC) has recently acquired a lot of interest in the optical wireless communication (OWC) community. The OWC channel has variable characteristics. Hence, there is a need for an adaptive modulation scheme to cope with the varying channel characteristics. Adaptive modulation requires the implementation of AMC at th...

This paper is mainly concerned with video watermarking as a tool to secure the video transmission process over wireless channels. In addition, the relatability of the communication process is guaranteed through a hybrid error control scheme. The watermarking depends on applying a hybrid structure of Block-based Singular Value Decomposition (B-SVD)...

Transfer learning (TL) appears to be a potential method for transferring information from general to specialized activities. Unfortunately, experimenting using various TL models does not yield good results. In this paper, we propose a model built from scratch with the Hough transform (HT) of constellation diagrams to improve modulation format recog...

Most current security and authentication systems are based on personal biometrics. The security problem is a major issue in the field of biometric systems. This is due to the use in databases of the original biometrics. Then biometrics will forever be lost if these databases are attacked. Protecting privacy is the most important goal of cancelable...

Beamforming design is a crucial stage in millimeter-wave systems with massive antenna arrays. We propose a deep learning network for the design of the precoder and combiner in hybrid architectures. The proposed network employs a parametric rectified linear unit (PReLU) activation function which improves model accuracy with almost no complexity cost...

Automatic Speaker Recognition (ASR) in mismatched conditions is a challenging task, since robust feature extraction and classification techniques are required. Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) is an efficient network that can learn to recognize speakers, text-independently, when the recording circumstances are similar. Unf...

Nowadays, biometric systems have replaced password-or token-based authentication systems in many fields to improve the security level. However, biometric systems are also vulnerable to security threats. Unlike passwords, biometric templates cannot be replaced if lost or compromised. To deal with issue of compromising biometric templates, template p...

Since the optimization process constitutes a great step in solving complex real world problems, the development of novel optimization algorithms is one of the growing interest topics that attracted researchers in the recent decades. This paper presents the hybridization of bio-inspired Biogeography Based Optimization (BBO) algorithm and physics-ins...

The phrase "anomaly detection" is often used to refer to any technique that seeks to find samples that differ from expected patterns. Depending on the availability of data labels, the types of abnormalities, and the applications, many anomaly detection models are developed. This study aims to give a well-organized and thorough review of anomaly det...

Brain tumors are a serious health issue that affects many people’s lives. Such a tumor, which is either benign or malignant, can be fatal if malignant cells are not correctly diagnosed. According to the most recent human health care analysis system, the number of brain tumor patients has climbed dramatically and is now the 10th top cause of death....

Low-frequency signals comprise different types such as Electroencephalogram (EEG), gyroscope and seismic signals. Processing of EEG signals is performed for tasks such as seizure prediction and detection. On the other hand, processing of seismic and gyroscope signals is performed for tasks such as activity classification. This paper presents two ef...

The Underwater Acoustic (UWA) wireless communication system is considered one of the most challenging systems for data transmission. The Orthogonal Frequency Division Multiplexing (OFDM) system promises numerous benefits, including high spectrum efficiency and inter-Symbol interference mitigation. But, it is very sensitive to Carrier Frequency Offs...

Medical image fusion is a process that aims to merge the important information from images with different modalities of the same organ of the human body to create a more informative fused image. In recent years, deep learning (DL) methods have achieved significant breakthroughs in the field of image fusion because of their great efficiency. The DL...

One of the critical challenges in multicarrier‐based systems is peak to average power ratio (PAPR). Recently, Filter Bank Multicarrier (FBMC) is proved to be a promising candidate that can replace the traditional orthogonal multiplexing division (OFDM) scheme due to its better spectral efficiency, reducing both inter‐channel interference (ICI) and...

This paper proposes a simplified fractal image compression algorithm which is implemented on a block by block basis. This algorithm achieves a compression ratio of up to 1:10 with a peak signal to noise ratio (PSNR) as high as 35dB. The idea of the proposed algorithm is based on the segmentation of the image, first, into blocks to setup reference b...

Transfer learning appears to be a potential method for transferring information from general to specialized activities. Unfortunately, experimenting using various transfer learning models does not yield good results. In this paper, we propose the utilization of the Hough transform (HT) to improve modulation format recognition. HT is utilized to est...

Recently, automatic modulation classification (AMC) has acquired a lot of interest in the optical communication community. Most optical wireless communication systems are intended to transmit multimedia content, especially video and speech signals. The optical wireless communication channel has variable characteristics. Hence, there is a need for a...

A brain tumor is an intracranial mass consisting of irregular growth of brain tissue cells. Medical imaging plays a vital role in discovering and examining the precise performance of organs The performance of object detection has increased dramatically by taking advantage of recent advances in deep learning. This paper presents a Convolutional Ne...

Detecting COVID-19 from medical images is a challenging task that has excited scientists around the world. COVID-19 started in China in 2019, and it is still spreading even now. Chest X-ray and Computed Tomography (CT) scan are the most important imaging techniques for diagnosing COVID-19. All researchers are looking for effective solutions and fas...

Infrared (IR) image sequences are acquired with certain types of cameras. These cameras give the sequence of images according to the heat distribution. With time, some deterioration of the quality of the sequence occurs due the thermal noise effect generated in the camera. This thermal noise effect leads to some sort of non-uniformity in the obtain...

Two schemes for optical wireless modulation format recognition (MFR), based on the orthogonal-triangular decomposition (OTD) and Hough transform (HT) of the constellation diagrams, are proposed in this paper. Constellation diagrams are obtained at optical signal-to-noise ratios (OSNRs) ranging from 5 to 30 dB for seven different modulation formats...

Recently, ground-penetrating radar (GPR) has been extended as a well-known area to investigate the subsurface objects. However, its output has a low resolution, and it needs more processing for more interpretation. This paper presents two algorithms for landmine detection from GPR images. The first algorithm depends on a multi-scale technique. A Ga...

Speaker recognition is one of several biometric recognition systems owing to its high importance in numerous applications of security and telecommunications. The key aspiration of speaker recognition systems is to know who is speaking depending on voice characteristics. This paper presents an extensive study of speaker recognition in both text-depe...

Higher data rate, increased capacity, higher mobility, lower latency and better quality are the mobile communication prime objectives need to improve in the near future. This paper proposes the suggested different modulation techniques for future fifth generation mobile networks (5G) which are universal filtered multicarrier (UFMC), filter bank mul...

Beamforming design is a crucial stage in millimeter-wave systems with massive antenna arrays. We propose a deep learning network for the design of the precoder and combiner in hybrid architectures. The proposed network employs a parametric rectified linear unit (PReLU) activation function which improves model accuracy with almost no complexity cost...

High-speed wireless communication is necessary in our personal lives, in both working and living spaces. This paper presents a scheme for wireless optical modulation format recognition (MFR) based on the Hough transform (HT). The HT is used to project constellation diagrams onto another space for efficient feature extraction. Constellation diagrams...

Future wireless networks are researching how to fulfill the growing demand for wireless optical communication. The increased usage of mobile devices and sensors in the real world has resulted in this increasing demand. The fifth-generation (5G) wireless network is the most promising wireless network in the future, with the potential to improve vari...

Deep learning is one of the most promising machine learning techniques that revolutionalized the artificial intelligence field. The known traditional and convolutional neural networks (CNNs) have been utilized in medical pattern recognition applications that depend on deep learning concepts. This is attributed to the importance of anomaly detection...

In this paper, we investigate and enhance the performance of data transmission using a hybrid underwater and terrestrial system with low‐complexity linear equalization. Due to the low speed, salinity, water depth, pH degree, and water temperature variations, underwater acoustic communication has become one of the most challenging technologies in th...

Corona Virus Disease 19 (COVID-19) firstly spread in China since December 2019. Then, it spread at a high rate around the world. Therefore, rapid diagnosis of COVID-19 has become a very hot research topic. One of the possible diagnostic tools is to use a deep convolution neural network (DCNN) to classify patient images. Chest X-ray is one of the mo...

In the Artificial Intelligence (AI) field, the deep learning is considered a method falls in the wide machine learning algorithms family based on the learning principle. The known traditional and Conventional Neural Networks (CNNs) have been utilized in the pattern recognition techniques based on the deep learning concepts from different images. Du...

In this paper, a new non-redundant three-layer peak-to-average power ratio (PAPR) reduction technique is proposed for filter bank multicarrier communication based visible light communication (FBMC based VLC) systems. In the proposed technique, the FBMC based VLC data signal is overlapped with two new non-redundant signals. The initial-layer signals...

Among all types of biometric recognition technologies, speaker identification has been considered as one of the most popular technologies due to simplicity and ability to capture and encode speech signals. However, biometric features may be misused by third parties. Hence, these features should be secured through the generation of revocable biometr...

Due to the complex structure of the brain, detecting tumor areas on magnetic resonance images of the brain has always been an interesting topic. Therefore, various imaging techniques have been used to detect objects and with the recent advances in deep learning, the performance of object detection has been greatly improved. In this paper, a propose...

More recently, biometric systems have spread for modern security applications. Unfortunately, these systems have experienced several attempts of hacking. If biometric databases are compromised and stolen, biometrics in these databases will be lost forever. Consequently, there is an immediate need to introduce new upgradable biometric systems. The c...

This paper presented a study for the feasibility of using spectrogram features generated from CNNs to recognize speakers. Both text-dependent and text-independent recognition systems have been presented and studied in the presence of degradation phenomena such as noise and reverberation. The effect of reverberation is noticeable in the recognition...

Multimodal medical image fusion aims to reduce insignificant information and improve clinical diagnosis accuracy. The purpose of image fusion is to retain salient image features and detail information of multiple source images to yield a more informative fused image. A hybrid algorithm based on both pixel and feature levels of multimodal medical im...

Gyroscopes are sensors that are used for motion measurement. They are generally used to measure rotation rate of moving equipment. There are different types of gyroscopes including mechanical, micro-electromechanical and optical gyroscopes. Gyroscope signal suffers from internal noise due to internal device operation and external noise of the envir...

Gyroscopes are sensors that are used for motion measurement. They are generally used to measure rotation rate of moving equipment. There are different types of gyroscopes including mechanical, micro-electromechanical and optical gyroscopes. Gyroscope signal suffers from internal noise due to internal device operation and external noise of the envir...

Optical wireless communication (OWC) technology is one of several alternative technologies for addressing the radio frequency limitations for applications in both indoor and outdoor architectures. Indoor optical wireless systems suffer from noise and intersymbol interference (ISI). These degradations are produced by the wireless channel multipath e...

The mid-symbol antenna transition (MAT) approach reduces the number of transmitter antennas in spatial modulation (SM) systems. This paper studies the performance of MAT technique over correlated and uncorrelated wireless channels. We focus on the scenario wherein the channel consists of multiple paths with a line of sight component, i.e., Rician f...

The paper presents an improvement of the watermark extraction in speech signal watermarking. The noise added to the speech signal during transmission affects the efficiency of the watermark extraction. Removing this noise may aid to enhance the extraction process. There are methods of the speech signal enhancement, which aims to reduce the noise di...

Generally, most blind signal separation algorithms deal with the separation problem in the absence of noise. The presence of noise degrades the performance of separated signals. This paper deals with the problem of blind separation of audio signals from noisy mixtures. Blind signal separation algorithm is applied on the discrete cosine transform, t...

In this paper, we present hybrid watermarking and error control techniques for reliable cornea and infrared frame communication through wireless networks in Internet of Things (IoT) applications. In the proposed watermarking technique, two stages of Singular Value Decomposition (SVD) watermarking are used. In the embedding stage, two watermark imag...

Recently, a novel spatial modulation (SM) scheme; termed Mid-symbol Antenna transition (MAT) spatial modulation, was developed to reduce the number of utilized transmitting antennas and improve the average bit error rate (ABER) performance. In this paper, the structure of the original MAT is extended to adapt Double-antenna transitions (DAT) during...

Multimodality medical image fusion is the process of combining multiple images from single or multiple modalities of imaging. Medical image fusion methods are adopted to increase the quality of medical images by attaining the salient features in the fusion results. Hence, they raise the clinical applicability of medical images for appraisal and dia...

This paper presents a patient-specific approach for electroencephalography (EEG) channel selection and seizure prediction based on statistical probability distributions of the EEG signals. This approach has two main phases; training and testing phases. In the training phase, few hours of multi-channel nature for each patient representing normal, pr...

This paper presents multi-level security scheme for images transmission, by applying signature scheme with encryption scheme. Signature is based on Discrete Cosine Transform (DCT) and Encoding using Double Random Phase Encoding (DRPE). The proposed multi-level scheme exploits the benefit of signature and encryption, which give strong images against...

This article is mainly concerned with COVID-19 diagnosis from X-ray images. The number of cases infected with COVID-19 is increasing daily, and there is a limitation in the number of test kits needed in hospitals. Therefore, there is an imperative need to implement an efficient automatic diagnosis system to alleviate COVID-19 spreading among people...

The implementation of the Orthogonal Frequency Division Multiplexing (OFDM) can be achieved using Inverse Discrete Cosine Transform (IDCT), and DCT instead of Inverse Discrete Fourier Transform (IDFT), and DFT. The Carrier Frequency Offset (CFO) is the main issue of the OFDM system. One of the aims to mitigate the CFO effect and improve the Bit‐Err...

The conventional Orthogonal Frequency Division Multiplexing (OFDM) can be simply implemented using Inverse Discrete Fourier Transform (IDFT), and DFT instead of bank of modulator and bank of demodulator, respectively. However, the OFDM can be modified using chaotic interleaving that reduces the 1-Dimension (1-D), and 2-Dimension (2-D) burst errors,...

Gyroscopes are sensors that are used for motion measurement. They are generally used to measure rotation rate of moving equipment. There are different types of gyroscopes including mechanical, micro-electromechanica and optical gyroscopes internal noise due to internal device operation and external noise of the environment. This paper presents a pr...

Abstract: In wireless radio communication systems, equalisation is one of the most important algorithms to improve the bite-rror-rate performance. The linear zero-forcing equalisers suffer from noise enhancement. The linear minimum mean square error equalisers suffer from large complexity and require the estimation of the signal-to-noise ratio to w...

Speaker recognition revolution has lead to the inclusion of speaker recognition modules in several commercial products. Most published algorithms for speaker recognition focus on text-dependent speaker recognition. In contrast, text-independent speaker recognition is more advantageous as the client can talk freely to the system. In this paper, text...

Filter bank multicarrier (FBMC) is a new waveform candidate in the visible light communication system (VLC). FBMC is a particular sort of multi-carrier modulation that can be viewed as an option in contrast to orthogonal frequency division multicarrier (OFDM) with CP (cyclic prefix). The point is to defeat some innate disadvantages of the normally...

The optimal placement of the RFID readers inaugurates an ongoing research field, namely the RFID network planning (RNP). The main issue in the RNP is to know how many readers have to be used and what is their best distribution that guarantees fulfillment of multiple objectives. The common RNP objectives are the optimal coverage, readers’ interferen...

Nowadays, optimization has become a brand methodology for different applications. One of the most promising fields for application of optimization is the image processing field, especially image fusion. A new effective deterministic optimization technique is the modified central force optimization (MCFO) that overcomes the low convergence rate draw...

This paper investigates the effect of both decoding and decompression on the Speaker Identification (SI) in a remote access system. The coding and compression processes are used for the communication purpose as a normal action taken for voice communication over Internet or mobile networks. In the proposed system, the speech signal is coded by Linea...

Anomaly detection is a very vital area in medical signal and image processing due to its importance in automatic diagnosis. This paper presents three efficient anomaly detection approaches for applications related to Electroencephalogram (EEG) signal processing and retinal image processing. The first approach depends on the utilization of Scale-Inv...

Gyroscopes are sensors that are used for motion measurement. They are generally used to measure rotation rate of moving equipment. There are different types of gyroscopes including mechanical, micro electro-mechanical (MEMS) and optical gyroscopes. Gyroscope signal suffers from internal noise due to internal device operation and external noise of t...

Image forgery detection is the basic key to solve many problems, especially social problems such as those in Facebook, and court cases. The common form of image forgery is the copy-move forgery, in which a section of the image is copied and pasted in another location within the same image. In this type of image forgery, it is easy to perform forger...

The early discovery of the disease is a great achievement in management of the cornea. This paper presents an efficient approach for the classification of normal and abnormal corneal patterns based on deep learning. Convolutional Neural Networks (CNNs) are utilized for this purpose. The CNN model built for this purpose comprises 5 layers. The class...