
Hossam M KasemTanta University · Department of Electronics Engineering and Communication Engineering
Hossam M Kasem
Associate Professor at Faculty of Engineering Tanta University
About
34
Publications
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185
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Introduction
Hossam M Kasem currently works at the Department of Electronics Engineering and Communication Engineering, Tanta University. Hossam does research in Communication Engineering, Electrical Engineering and Electronic Engineering. His Current Project is Deep learning applications in Multimedia analysis
Additional affiliations
September 2017 - present
September 2015 - September 2017
Faculty of Engineering,Tanta University
Position
- Professor (Assistant)
September 2015 - September 2017
Publications
Publications (34)
In order for cognitive radios to identify and take advantage of unused frequency bands, spectrum sensing is essential. Conventional techniques for spectrum sensing rely on extracting features from received signals at specific locations. However, convolutional neural networks (CNNs) and recurrent neural networks (RNNs) have recently demonstrated pro...
Side lobe level reduction (SLL) of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service (QOS) in recent and future wireless communication systems starting from 5G up to 7G. Furthermore, it improves the array gain and directivity, increasing the detection range and angular resolution of radar sys...
This paper presents accurate approximation expressions for the outage and secrecy outage probabilities of relay-assisted free-space optical (FSO) communication links utilizing unmanned aerial vehicles (UAVs). We consider the effects of weather attenuation and random fluctuations of UAVs’ orientations and positions. The obtained expressions are appl...
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...
Magnetic resonance imaging (MRI) combined with artificial intelligence (AI) algorithms to detect brain tumors is one of the important medical applications. In this study, a Convolutional neural network (CNN) model is proposed to detect meningioma and pituitary, which was tested with a dataset consisting of two categories of tumors with 1,800 MRI im...
It is crucial to have a dependable and precise channel model in order to study the properties of millimeter wave (mmWave) propagation. The Quasi-deterministic (QD) channel model is employed in this viewpoint, which describes the propagation of mm-Wave as a group of reflected and scattered rays originating from a complex environmental setup. These r...
In the presence of noise in communication systems, constellation diagram points are scattered to the extent that may make the modulation classification a difficult task. With the plethora of applications of machine and deep learning, several communication systems have adopted machine and deep learning to solve some classical detection and classific...
In the presence of noise in communication systems, constellation diagram points are scattered to the extent that may make the modulation classification
a difficult task. With the plethora of applications of machine and deep learning,
several communication systems have adopted machine and deep learning to
solve some classical detection and classific...
Compressed sensing (CS) represents an efficient framework to simultaneously acquire and compress images/signals while reducing acquisition time and memory requirements to process or transmit them. Specifically, CS is able to recover an image from a random measurements. Recently, deep neural networks (DNNs) are exploited not only to acquire and comp...
Massive multiple-input multiple-output (M-MIMO) is one of the main 5G-enabling technologies that promise to increase cell throughput and reduce multiuser interference. However, these abilities rely on exploiting the channel state information (CSI) feedback at base stations (BSs). One critical challenge is that the user equipment (UE) needs to retur...
In medical imaging, it is crucial to reduce the exposure time of the patient to the medical modality. Medical image compression has a significant role, including telemedicine, medical imaging, and video conferencing for consultation. One of the effective compression techniques, compressive sensing (CS), defined as a hypothesis to represent the info...
Recent technological advancement in computing technology, communication systems, and machine learning techniques provides opportunities to biomedical engineers to achieve the requirements of clinical practice. This requires storage and/or transmission of medical images with the conservation of the medical information over the communication channel....
Recently, there have been significant advances in image super-resolution based on generative adversarial networks (GANs) to achieve breakthroughs in generating more images with high subjective quality. However, there are remaining challenges needs to be met, such as simultaneously recovering the finer texture details for large upscaling factors and...
For many practical applications, it is essential to address both geometric corrections and missing information reconstruction of face images and natural images. However, it is unfavorable to separate the problem into two sub-tasks due to error accumulations of sequential tasks. In this paper, we propose a novel robust missing information reconstruc...
For many practical applications, it is essential to address both geometric corrections and missing information reconstruction of face images and natural images. However, it is unfavorable to separate the problem into two sub-tasks due to error accumulations of sequential tasks. In this paper, we propose a novel robust missing information reconstruc...
In general, existing research on single image super-resolution does not consider the practical application that, when image transmission is over noisy channels, the effect of any possible geometric transformations could incur significant quality loss and distortions. To address this problem, we present a new and robust super-resolution method in th...
This paper presents an improvement for a bit error rate (BER) performance in a free-space optical communication system over log-normal fading channel and misalignment effect, by using single-input multiple-output (SIMO) technique with maximal ratio combining. Differential phase shift keying with subcarrier intensity modulation is applied. The BER c...
Highdata rate cognitive radio (CR) systems require high speed Analog-to-Digital Converters (ADC). This requirement imposes many restrictions on the realization of the CR systems. The necessity of high sampling rate can be significantly alleviated by utilizing analog to information converter (AIC). AIC is inspired by the recent theory of Compressive...
The Twentieth IEEE Symposium on Computers and Communications (ISCC 2015)
In this paper, we propose using different quantization values, including 1-bit com-pressed sensing for perceptual audio signal compression in perceptual systems[1], in order to clarify the effect of the quantization process on the achievable quality of audio signal. Simulations results show that reasonable performance is achieved for different quan...
I. Introduction Compressed sensing (CS) is a new signal acquisition technique aims to reduce the number of the measurements required to acquire the signal that are sparse or approximately sparse in some basis [1]. In this paper we propose to use one-bit quantized perceptual CS model for audio compression, where the sign of the random measurements i...
Compressed sensing (CS) is a new signal acquisition technique aims to reduce the number of the measurements required to acquire the signal that are sparse or approximately sparse in some basis. Compressed Sensing has many applications in the field of Signal processing, Specially in signal compression. CS provides good quality of the restored signal...
In K-best sphere decoding algorithm (KB), the number of survivor paths K, can be integer values in all tree levels. A certain complexity is provided for each value of K. In this letter, a variant of the K-best sphere decoding algorithm for uncoded MIMO channels is proposed, namely, flexible fractional K-best algorithm (FFKB). The FFKB provides a de...
Sparse signal processing has become central in many communications and multimedia processing applications. Techniques such as Compressed Sensing(CS) and Sparse Fast Fourier Transform (SFFT) provide good quality of the restored signal even when the signal is not completely sparse even also at high compression ratio. In this work, we examine the effe...
Audio compression has become one of the basic multimedia technologies.
Choosing an efficient compression scheme that is capable of preserving the
signal quality while providing a high compression ratio is desirable in the
different standards worldwide. In this paper we study the application of two
highly acclaimed sparse signal processing algorithm...
K-best sphere decoding algorithm (KBA) is used to approach near-maximum-likelihood (ML) performance for multiple-input–multiple-output (MIMO) detection with lower complexity than maximum-likelihood (ML) method. In KBA, the value of survivor paths K, can be fixed values only in all tree levels. These fixed values of K's give a certain performances a...
Image transmission has evolved as an important research branch in multimedia broadcasting
communication systems in the last few decades. This paper is devoted to the transmission of encrypted
images over Orthogonal Frequency Division Multiplexing (OFDM) systems. Encryption is carried out with
both Baker and logistic maps, while a chaotic Baker m...
. In this paper, a newefficient image encryption technique ispresented.It is based on a combination
between chaotic Arnold’s cat map and the international data encryption algorithm (IDEA) in order to meet
therequirements of secure image transfer. First, the IDEA accepts a 128 bits secret key which is used to
generate an encryption key. The encry...
Image transmission takes place as an important research branch in multimedia broadcasting communication systems in the last decade. Our paper presents image transmission over a FFT-OFDM (Fast Fourier Transform Orthogonal Frequency Division Multiplexing). The need for encryption techniques increase with the appearance of the expression which said th...