Qaisar Abbas

Qaisar Abbas
Imam Muhammad bin Saud Islamic University · Department of Computer Science

PhD

About

94
Publications
52,526
Reads
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2,665
Citations
Introduction
Qaisar Abbas currently works at the Department of Computer Science, Imam Muhammad bin Saud Islamic University. Their current project is 'Retinal fundus image analysis'.
Additional affiliations
August 2014 - present
Imam Muhammad bin Saud Islamic University
Position
  • Professor (Assistant)
March 2011 - August 2013
National Textile University
Position
  • Professor (Assistant)
August 2014 - present
Imam Muhammad bin Saud Islamic University
Position
  • Professor (Assistant)
Education
September 2008
Huazhong University of Science and Technology
Field of study
  • Biomedical image Processing
March 2002 - September 2005
B.Z.U
Field of study
  • Computer Science

Publications

Publications (94)
Article
Removal and restoration of hair and hair-like regions within skin lesion images is needed so features within lesions can be more effectively analyzed for benign lesions, cancerous lesions, and for cancer discrimination. This paper refers to “melanoma texture” as a rationale for supporting the need for the proposed hair detection and repair techniqu...
Article
Pattern classification of dermoscopy images is a challenging task of differentiating between benign melanocytic lesions and melanomas. In this paper, a novel pattern classification method based on color symmetry and multiscale texture analysis is developed to assist dermatologists' diagnosis. Our method aims to classify various tumor patterns using...
Article
Mass segmentation in mammograms is a challenging task due to problems such as low contrast, ill-defined, fuzzy or spiculated borders, and the presence of intensity inhomogeneities. These facts complicate the development of computer-aided diagnosis (CAD) systems to assist radiologists. In this paper, a novel mass segmentation algorithm for mammogram...
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Particularly in the field of computer vision, Deep Learning (DL) models have demonstrated superior performance over classical Machine Learning (ML) at recognizing patterns in complicated and high-dimensional data. Recent years have seen a significant increase in interest in the use of DL for automated categorization and early diagnosis of Alzheimer...
Article
Biometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric systems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale train...
Preprint
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The scalability of Blockchain is a significant factor that requires attention for it to compete with traditional solutions. One of the main concerns in the scalability aspect of Blockchain is throughput and latency. The slow transaction verification process is one of the primary causes of this issue in the founding systems and their descendant solu...
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Biometric authentication is a widely used method for verifying individuals’ identities using photoplethysmography (PPG) cardiac signals. The PPG signal is a non-invasive optical technique that measures the heart rate, which can vary from person to person. However, these signals can also be changed due to factors like stress, physical activity, illn...
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When the mutation affects the melanocytes of the body, a condition called melanoma results which is one of the deadliest skin cancers. Early detection of cutaneous melanoma is vital for raising the chances of survival. Melanoma can be due to inherited defective genes or due to environmental factors such as excessive sun exposure. The accuracy of th...
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The primary objective of this study is to develop an advanced, automated system for the early detection and classification of leaf diseases in potato plants, which are among the most cultivated vegetable crops worldwide. These diseases, notably early and late blight caused by Alternaria solani and Phytophthora infestans, significantly impact the qu...
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Developing a simple and efficient attack detection system for ensuring the security of cloud systems against cyberthreats is a crucial and demanding process in the present time. In traditional work, various machine-learning-based detection methodologies have been developed for securing the cloud network. However, those methodologies face the compli...
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The lungs are critical components of the respiratory system because they allow for the exchange of oxygen and carbon dioxide within our bodies. However, a variety of conditions can affect the lungs, resulting in serious health consequences. Lung disease treatment aims to control its severity, which is usually irrevocable. The fundamental objective...
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It is difficult for clinicians or less-experienced ophthalmologists to detect early eye-related diseases. By hand, eye disease diagnosis is labor-intensive, prone to mistakes, and challenging because of the variety of ocular diseases such as glaucoma (GA), diabetic retinopathy (DR), cataract (CT), and normal eye-related diseases (NL). An automated...
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In the contemporary digital landscape, web search functions as a pivotal conduit for information dissemination. Nevertheless, blind users (BUs) encounter substantial barriers in leveraging online services, attributable to intrinsic deficiencies in the information structure presented by online platforms. A critical analysis reveals that a considerab...
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A well-known eye disorder called diabetic retinopathy (DR) is linked to elevated blood glucose levels. Cotton wool spots, confined veins in the cranial nerve, AV nicking, and hemorrhages in the optic disc are some of its symptoms, which often appear later. Serious side effects of DR might include vision loss, damage to the visual nerves, and obstru...
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The Internet of Things (IoT) has significantly benefited several businesses, but because of the volume and complexity of IoT systems, there are also new security issues. Intrusion detection systems (IDSs) guarantee both the security posture and defense against intrusions of IoT devices. IoT systems have recently utilized machine learning (ML) techn...
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Convolutional neural network (CNN) models have been extensively applied to skin lesions segmentation due to their information discrimination capabilities. However, CNNs’ struggle to capture the connection between long-range contexts when extracting deep semantic features from lesion images, resulting in a semantic gap that causes segmentation disto...
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In recent years, advances in deep learning (DL) techniques for video analysis have developed to solve the problem of real-time processing. Automated face recognition in the runtime environment has become necessary in video surveillance systems for urban security. This is a difficult task due to face occlusion, which makes it hard to capture effecti...
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User authentication has become necessary in different life domains. Traditional authentication methods like personal information numbers (PINs), password ID cards, and tokens are vulnerable to attacks. For secure authentication, methods like biometrics have been developed in the past. Biometric information is hard to lose, forget, duplicate, or sha...
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Data sharing with additional devices across wireless networks is made simple and advantageous by the Internet of Things (IoT), an emerging technology. However, IoT systems are more susceptible to cyberattacks because of their continued growth and technological advances, which could lead to powerful assaults. An intrusion detection system is one of...
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Cardiovascular disorders are often diagnosed using an electrocardiogram (ECG). It is a painless method that mimics the cyclical contraction and relaxation of the heart’s muscles. By monitoring the heart’s electrical activity, an ECG can be used to identify irregular heartbeats, heart attacks, cardiac illnesses, or enlarged hearts. Numerous studies...
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Citation: Sajid, M.Z.; Hamid, M.F.; Youssef, A.; Yasmin, J.; Perumal, G.; Qureshi, I.; Naqi, S.M.; Abbas, Q. Abstract: Diabetes is a widely spread disease that significantly affects people's lives. The leading cause is uncontrolled levels of blood glucose, which develop eye defects over time, including Diabetic Retinopathy (DR), which results in se...
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Computed tomography (CT) scans, or radiographic images, were used to aid in the early diagnosis of patients and detect normal and abnormal lung function in the human chest. However, the diagnosis of lungs infected with coronavirus disease 2019 (COVID-19) was made more accurately from CT scan data than from a swab test. This study uses human chest r...
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A dermatologist-like automatic classification system is developed in this paper to recognize nine different classes of pigmented skin lesions (PSLs), using a separable vision transformer (SVT) technique to assist clinical experts in early skin cancer detection. In the past, researchers have developed a few systems to recognize nine classes of PSLs....
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A student’s engagement in a real classroom environment usually varies with respect to time. Moreover, both genders may also engage differently during lecture procession. Previous research measures students’ engagement either from the assessment outcome or by observing their gestures in online or real but controlled classroom environments with limit...
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Ovarian cancer ranks as the fifth leading cause of cancer-related mortality in women. Late-stage diagnosis (stages III and IV) is a major challenge due to the often vague and inconsistent initial symptoms. Current diagnostic methods, such as biomarkers, biopsy, and imaging tests, face limitations, including subjectivity, inter-observer variability,...
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Hypertensive retinopathy (HR) is a serious eye disease that causes the retinal arteries to change. This change is mainly due to the fact of high blood pressure. Cotton wool patches, bleeding in the retina, and retinal artery constriction are affected lesions of HR symptoms. An ophthalmologist often makes the diagnosis of eye-related diseases by ana...
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Consumer knowledge of the goods produced or processed by the numerous suppliers and processors is still relatively low due to the growing complexity of the structure of pharmaceutical supply chains. Information asymmetry in the pharmaceutical sector has an effect on welfare, sustainability, and health. (1) Background: In this respect, we wanted to...
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In recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study propose...
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The diagnosis of eye disease through deep learning (DL) technology is the latest trend in the field of artificial intelligence (AI). Especially in diagnosing pathologic myopia (PM) lesions, the implementation of DL is a difficult task because of the classification complexity and definition system of PM. However, it is possible to design an AI-based...
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Skin cancer develops due to the unusual growth of skin cells. Early detection is critical for the recognition of multiclass pigmented skin lesions (PSLs). At an early stage, the manual work by ophthalmologists takes time to recognize the PSLs. Therefore, several “computer-aided diagnosis (CAD)” systems are developed by using image processing, machi...
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The COVID-19 epidemic has created highly unprocessed emotions that trigger stress, anxiety, or panic attacks. These attacks exhibit physical symptoms that may easily lead to misdiagnosis. Deep-learning (DL)-based classification approaches for emotion detection based on electroencephalography (EEG) signals are computationally costly. Nowadays, limit...
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Mental deterioration or Alzheimer’s (ALZ) disease is progressive and causes both physical and mental dependency. There is a need for a computer-aided diagnosis (CAD) system that can help doctors make an immediate decision. (1) Background: Currently, CAD systems are developed based on hand-crafted features, machine learning (ML), and deep learning (...
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The major cause of death worldwide is due to cardiovascular disorders (CVDs). For a proper diagnosis of CVD disease, an inexpensive solution based on phonocardiogram (PCG) signals is proposed. (1) Background: Currently, a few deep learning (DL)-based CVD systems have been developed to recognize different stages of CVD. However, the accuracy of thes...
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Hypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. I...
Article
Due to the wide range of diseases and imaging modalities, a retrieving system is a challenging task to access the corresponding clinical cases from a large medical repository on time. Several intelligent systems are developed to recognize medical images based on various machine learning algorithms such as deep learning and transfer learning methods...
Article
Semantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of...
Article
Due to the wide range of diseases and imaging modalities, a retrieving system is a challenging task to access the corresponding clinical cases from a large medical repository on time. Several computer-aided systems (CADx) are developed to recognize medical imaging modalities (MIM) based on various standard machine learning (SML) and advanced deep l...
Article
Biometrics is a powerful tool for identifying and authenticating persons based on their unique characteristics. Finger vein (FV) seems to be an emerging biometric of all types of hand-based biometrics, which have garnered considerable interest because of the extensive information and ease of implementation. As the FV system has grown in popularity,...
Article
Glaucoma, diabetic retinopathy, diabetic hypertension (DHR), Cataract, and age-related macular degeneration are some of the most common and important retinal diseases. A permanent vision loss occurs if these diseases are not discovered at an early stage. It is illustrated by numerous abnormalities in the retina such as microaneurysms (MA), hard exu...
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Diabetic retinopathy (DR) diagnosis through digital fundus images requires clinical experts to recognize the presence and importance of many intricate features. This task is very difficult for ophthalmologists and time-consuming. Therefore, many computer-aided diagnosis (CAD) systems were developed to automate this screening process of DR. In this...
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The stage and duration of hypertension are connected to the occurrence of Hypertensive Retinopathy (HR) of eye disease. Currently, a few computerized systems have been developed to recognize HR by using only two stages. It is difficult to define specialized features to recognize five grades of HR. In addition, deep features have been used in the pa...
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Traffic accidents are caused by driver fatigue or distraction in many cases. To prevent accidents, several low-cost hypovigilance (hypo-V) systems were developed in the past based on a multimodal-hybrid (physiological and behavioral) feature set. Similarly in this paper, real-time driver inattention and fatigue (Hypo-Driver) detection system is pro...
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Several hypovigilance detection systems (HDx) were developed to avoid road-side accidents due to driver fatigue. They have suffered from several limitations. Notably many of these are focused on center-head position to define an area of interest (often referred to as PERCLOS (percentage eye closure)) without considering the face occlusion problem,...
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Retinal fundus image analysis (RFIA) for diabetic retinopathy (DR) screening can be used to reduce the risk of blindness among diabetic patients. The RFIA screening programs help the ophthalmologists to cope with this paramount visual impairment problem. In this article, an automatic recognition of the DR stage is proposed based on a new multi-laye...
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Biometric deals with the verification and identification of a person based on behavioural and physiological traits. This article presents recent advances in physiological-based biometric multimodalities, where we focused on finger vein, palm vein, fingerprint, face, lips, iris, and retina-based processing methods. The authors also evaluated the arc...
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Internet of things (IoT) cloud-based applications deliver advanced solutions for smart cities to decrease traffic accidents caused by driver fatigue while driving on the road. Environmental conditions or driver behavior can ultimately lead to serious roadside accidents. In recent years, the authors have developed many low-cost, computerized, driver...
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High blood pressure and diabetes are associated with a retinal abnormality known as Hypertensive Retinopathy (HR). The severity-level and duration of hypertension are straightly related to the incidence of HR-eye disease. The HR damages the pathological lesions of eyes such as arteriolar narrowing, retinal hemorrhage, macular edema, cotton wool spo...
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Road accidents mainly caused by the state of driver drowsiness. Detection of driver drowsiness (DDD) or fatigue is an important and challenging task to save road-side accidents. To help reduce the mortality rate, the "HybridFatigue" DDD system was proposed. This HybridFatigue system is based on integrating visual features through PERCLOS measure an...
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The Scientific community has been developing computer-aided detection systems (CADs) for automatic diagnosis of pigmented skin lesions (PSLs) for nearly 30 years. Several works have addressed this issue and obtained encouraging results, however, there has not been much focus on the pre-processing step, determining the relevance of the features cons...
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Diabetic retinopathy (DR) is a complication of diabetes that exists throughout the world. DR occurs due to a high ratio of glucose in the blood, which causes alterations in the retinal microvasculature. Without preemptive symptoms of DR, it leads to complete vision loss. However, early screening through computer-assisted diagnosis (CAD) tools and p...
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Real-time video objects detection, tracking, and recognition are challenging issues due to the real-time processing requirements of the machine learning algorithms. In recent years, video processing is performed by deep learning (DL) based techniques that achieve higher accuracy but require higher computations cost. This paper presents a recent sur...
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Vehicle monitoring is a challenging task for video-based intelligent transportation system (V-ITS). Nowadays, the V-ITS system has a significant socioeconomic impact on the development of smart cities and always demand to monitor different traffic parameters. It noticed that traffic accidents are exceeded throughout the world with the percentage of...
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Video scene analysis is a recent research topic due to its vital importance in many applications such as real-time vehicle activity tracking, pedestrian detection, surveillance, and robotics. Despite its popularity, the video scene analysis is still an open challenging task and require more accurate algorithms. However, the advances in deep learnin...
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Stemming is the basic operation in Natural language processing (NLP) to remove derivational and inflectional affixes without performing a morphological analysis. This practice is essential to extract the root or stem. In NLP domains, the stemmer is used to improve the process of information retrieval (IR), text classifications (TC), text mining (TM...
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The Appearance Models (AMs) are widely used in many applications related to face recognition, expression analysis and computer vision. Despite its popularity, the AMs are not much more accurate due to partial occlusion. Therefore, the authors have developed Robust Normalization Inverse Compositional Image Alignment (RNICIA) algorithm to solve parti...
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Diabetic retinopathy (DR) is leading cause of blindness among diabetic patients. Recognition of severity level is required by ophthalmologists to early detect and diagnose the DR. However, it is a challenging task for both medical experts and computer-aided diagnosis systems due to requiring extensive domain expert knowledge. In this article, a nov...
Article
Computer-aided diagnostics (CAD) systems for automatic detection of lung cancer or lung-related diseases have highly depended on the segmentation accuracy of differential structures from computed tomography (CT) scan images. By detection of differential structures such as right/left Lungs, lung nod-ules, human airways and pulmonary trees, the new s...
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Finding non-coding RNA (ncRNA) genes has emerged over the past few years as a cutting-edge trend in bioinformatics. There are numerous computational intelligence (CI) challenges in the annotation and interpretation of ncRNAs because it requires a domain-related expert knowledge in CI techniques. Moreover, there are many classes predicted yet not ex...
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The development of a computer-aided diagnosis (CAD) system for differentiation between benign and malignant mammographic masses is a challenging task due to the use of extensive pre- and post-processing steps and ineffective features set. In this paper, a novel CAD system is proposed called DeepCAD, which uses four phases to overcome these problems...
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A differentiation between all types of melanocytic and non-melanocytic skin lesions (MnM–SK) is a challenging task for both computer-aided diagnosis (CAD) and dermatologists due to the complex structure of patterns. The dermatologists are widely using pattern analysis as a first step with clinical attributes to recognize all categories of pigmented...