Muhammad Sajjad

Visual sensor networks (VSNs) usually generate a low-resolution (LR) frame-sequence due to energy and processing constraints. These LR-frames are not very appropriate for use in certain surveillance applications. It is very important to enhance the resolution of the captured LR-frames using resolution enhancement schemes. In this paper, an effectiv...

Digital investigations are very difficult to conduct from low-quality images generated by low-quality sensors. Therefore, we present a novel superresolution (SR) scheme that applies SR and denoising simultaneously, using the concept of sparse representation. For SR, a low-resolution (LR) input image is scaled up using our recently described adaptiv...

This paper proposes a cost-effective and edge-directed image super-resolution scheme. Image super-resolution (image magnification) is an enthusiastic research area and is desired in a variety of applications. The basic idea of the proposed scheme is based on the concept of multi-kernel approach. Various stencils have been defined on the basis of ge...

Leukocytes are pivotal markers in health, crucial for diagnosing diseases like malaria and viral infections. Peripheral blood smear tests provide pathologists with vital insights into various medical conditions. Manual leukocyte counting is challenging and error-prone due to their complex structure. Accurate segmentation and classification of leuko...

This article introduces a comprehensive multiagent prototype system designed to enhance the autonomous navigation capabilities of vehicles by incorporating numerous sensors and components. The system includes features such as an ultrasonic sensor for precise distance measurement, a specially crafted “SonarSpinner” with a wide 160° field of view, a...

Leukocytes, also called White Blood Cells (WBCs) or leucocytes, are the cells that play a pivotal role in human health and are vital indicators of diseases such as malaria, leukemia, AIDS, and other viral infections. WBCs detection and classification in blood smears offers insights to pathologists, aiding diagnosis across medical conditions. Tradit...

Wearable sensors-based human gait activity recognition (HGAR) has become increasingly popular for various healthcare applications, such as patient monitoring and postural instability analysis. Despite the promise shown by previous studies using deep and machine learning methods, many challenges remain to be addressed, such as limited stability and...

The aim of this study is to develop a cost-effective and efficient mobile robotic manipulator designed for decluttering objects in both domestic and industrial settings. To accomplish this objective, we implemented a deep learning approach utilizing YOLO for accurate object detection. In addition, we incorporated inverse kinematics to facilitate th...

Freezing of gait (FOG) is one of the most common manifestations of advanced Parkinson’s disease. It represents a sudden interruption of walking forward associated with an increased risk of falling and poor quality of life. Evolutionary algorithms, such as genetic programming (GP), have been effectively applied in modelling many real-world applicati...

The recognition of different activities in sports has gained attention in recent years for its applications in various athletic events, including soccer and cricket. Cricket, in particular, presents a challenging task for automatic activity recognition methods due to its closely overlapped activities such as cover drive, and pull short, to name a f...

Nowadays, the use of public transportation is reducing and people prefer to use private transport because of its low cost, comfortable ride, and personal preferences. However, personal transport causes numerous real-world road accidents due to the conditions of the drivers’ state such as drowsiness, stress, tiredness, and age during driving. In suc...

Vehicle license plate images are often low resolution and blurry because of the large distance and relative motion between the vision sensor and vehicle, making license plate identification arduous. The extensive use of expensive, high-quality vision sensors is uneconomical in most cases; thus, images are initially captured and then translated from...

The new COVID-19 variants of concern are causing more infections and spreading much faster than their predecessors. Recent cases show that even vaccinated people are highly affected by these new variants. The proactive nucleotide sequence prediction of possible new variants of COVID-19 and developing better healthcare plans to address their spread...

Intelligence and sustainability are two essential drivers for the development of current and future Intelligent Transportation Systems. On one hand, the complexity of vehicular ecosystems and the inherently risk-prone circumstances under which pedestrian and vehicles coexist call for the endowment of intelligent functionalities in almost all system...

This paper proposed a lightweight, efficient Convolution Neural Network model for automatic disaster recognition from aerial images. The model consists of a stack of convolutions and dense layers, and training incorporates several augmentation and data pre-processing techniques to improve the model’s generalisation. The model is evaluated on standa...

In this work, we propose an encoder-decoder-based automatic report generation system capable of generating radiology reports for chest x-rays. We tested five backbone Convolutional Neural Networks, namely VGG16, InceptionV3, Resnet50, MobileNet and NasNet mobile, to extract visual features and used Long Short-Term Long Memory (LSTM) to extract the...

In recent development of machine learning (ML)-based medical image analysis that have contributed to the prediction, planning, and early diagnostic process. Different chronic hermitic diseases like blood cancer/leukemia, AIDs, malaria, anemia and even COVID-19, all these are diagnoses via analyzing leucocytes or white blood cells (WBCs). Leucocytes...

Deep Learning models’ performance strongly correlate with availability of annotated data; however, massive data labelling is laborious, expensive, and error-prone when performed by human experts. Active Learning (AL) effectively handles this challenge by selecting the uncertain samples from unlabeled data collection, but the existing AL approaches...

Human interaction recognition (HIR) is challenging due to multiple humans’ involvement and their mutual interaction in a single frame, generated from their movements. Mainstream literature is based on three-dimensional (3-D) convolutional neural networks (CNNs), processing only visual frames, where human joints data play a vital role in accurate in...

Facial expression (FE) is the most natural and convincing source to communicate human emotions, providing valuable insides to the observer while assessing the emotional incongruities. In health care, the FE of the patient (specifically of neurological disorders (NDs) such as Parkinson’s, Stroke, and Alzheimer’s) can assist the medical doctor in eva...

Surveillance systems regularly create massive video data in the modern technological era, making their analysis challenging for security specialists. Finding anomalous activities manually in these enormous video recordings is a tedious task, as they infrequently occur in the real world. We proposed a minimal complex deep learning-based model named...

Conducting and evaluating continuous student feedback is essential for any quality enhancement cell (QEC) within an education institution. Students’ feedback based on their personal opinions can play a vital role in ensuring quality education. However, students’ subjective opinions are often ignored due to time constraints or a lack of adequate ana...

The coronavirus disease 2019 (COVID-19) pandemic has caused a major outbreak around the world with severe impact on health, human lives, and economy globally. One of the crucial steps in fighting COVID-19 is the ability to detect infected patients at early stages and put them under special care. Detecting COVID-19 from radiography images using comp...

The highly rapid spread of the current pandemic has quickly overwhelmed hospitals all over the world and motivated extensive research to address a wide range of emerging problems. The unforeseen influx of COVID-19 patients to hospitals has made it inevitable to deploy a rapid and accurate triage system, monitor progression, and predict patients at...

Cross-modal medical imaging techniques are predominantly being used in the clinical suite. The ensemble learning methods using cross-modal medical imaging adds reliability to several medical image analysis tasks. Motivated by the performance of deep learning in several medical imaging tasks, a deep learning-based denoising method Cross-Modality Gui...

Renewable energies use clean sources for energy generation and have the potential to balance the supply and demand of power. One of the best ways to save energy for high-demand time is to preserve it in a battery energy storage system (BESS). Various methods are presented in the last two decades for battery state of charge (SOC) estimation, however...

Due to the rapid development of artificial intelligence technology, industrial sectors are revolutionizing in automation, reliability, and robustness, thereby significantly increasing quality and productivity. Most of the surveillance and industrial sectors are monitored by visual sensor networks capturing different surrounding environment images....

Due to recent advances in the film industry, the production of movies has grown exponentially, which has led to challenges in what is referred to as discoverability: given the overwhelming number of choices, choosing which film to watch has become a tedious task for audiences. Movie summarization (MS) could help, as it presents the central theme of...

The salient events recognition of soccer matches in next-generation Internet of things (Nx-IoT) environment aims to analyze the performance of players/teams by the sports analytics and managerial staff. The embedded Nx-IoT devices carried by the soccer players during the match capture and transmit data to an Artificial Intelligence (AI)-assisted co...

Online learning environments (OLE) are gaining popularity, including learning management systems (LMS) and massive open online courses (MOOCs), which are the best modern alternate solutions available for education in the current era. The luxury to learn irrespective of geographical and temporal restrictions makes it an attractive resource. At the s...

Digital surveillance systems are ubiquitous and continuously generate massive amounts of data, and manual monitoring is required in order to recognise human activities in public areas. Intelligent surveillance systems that can automatically identify normal and abnormal activities are highly desirable, as these would allow for efficient monitoring b...

Smart home applications are ubiquitous and have gained popularity due to the overwhelming use of Internet of Things (IoT)-based technology. The revolution in technologies has made homes more convenient, efficient, and even more secure. The need for advancement in smart home technology is necessary due to the scarcity of intelligent home application...

With the emerging technologies of augmented reality (AR) and virtual reality (VR), the learning process in today’s classroom is much more effective and motivational. Overlaying virtual content into the real world makes learning methods attractive and entertaining for students while performing activities. AR techniques make the learning process easy...

Human action recognition in videos is an active area of research in computer vision and pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for human-behavior assessment and security purposes. The existing action recognition techniques are mainly using pre-trained weights of different AI architectures for the visual...

Virtual reality (VR) has been widely used as a tool to assist people by letting them learn and simulate situations that are too dangerous and risky to practice in real life, and one of these is road safety training for children. Traditional video- and presentation-based road safety training has average output results as it lacks physical practice a...

The accurate splice site prediction has several applications in the field of medical sciences and biochemistry. For instance, any mutation affecting the splice site will lead to genetic diseases and cancer such as Lynch syndrome and breast cancer. For this purpose, collecting the Ribonucleic acid (RNA) samples is an efficient and convenient method...

In current technological era, surveillance systems generate an enormous volume of video data on a daily basis, making its analysis a difficult task for computer vision experts. Manually searching for unusual events in these massive video streams is a challenging task, since they occur inconsistently and with low probability in real-world surveillan...

Smart home applications are pervasive and have gained popularity due to the overwhelming use of Internet of Things (IoT). The revolution in IoT technologies made homes more convenient, efficient and perhaps more secure. The need to advance smart home technology is necessary at this stage as IoT is abundantly used in automation industry. However, mo...

The industrial demands of immersive videos for virtual reality/augmented reality applications are crescendo, where the video stream provides a choice to the user viewing object of interest with the illusion of “being there”. However, in industry 4.0, streaming of such huge-sized video over the network consumes a tremendous amount of bandwidth, wher...

In computer vision, traditional machine learning (TML) and deep learning (DL) methods have significantly contributed to the advancements of medical image analysis (MIA) by enhancing prediction accuracy, leading to appropriate planning and diagnosis. These methods substantially improved the diagnoses of automatic brain tumor and leukemia/blood cance...

Security and privacy are essential requirements, and their fulfillment is considered one of the most challenging tasks for healthcare organizations to manage patient data using electronic health records. Electronic health records (clinical notes, images, and documents) become more vulnerable to breaching patients’ privacy when shared with an extern...

In the current technological era, energy-efficient buildings have a significant research body due to increasing concerns about energy consumption and its environmental impact. Designing an appropriate energy-efficient building depends on its layout, such as relative compactness, overall area, height, orientation, and distribution of the glazing are...

Multiview video summarization (MVS) has not received much attention from the research community due to inter-view correlations and views’ overlapping, etc. The majority of previous MVS works are offline, relying on only summary, and require additional communication bandwidth and transmission time, with no focus on foggy environments. We propose an...

Distributed intrusion detection systems (IDS) are primarily deployed across the network to monitor, detect, and report anomalies, as well as to respond in real-time. Predominantly, an IDS is equipped with a set of rules that it needs to infer to be able to perform efficient detection. However, generating false alarms is a major challenge in any IDS...

Human behavior analysis from big multimedia data has become a trending research area with applications to various domains such as surveillance, medical, sports, and entertainment. Facial expression analysis is one of the most prominent clues to determine the behavior of an individual, however, it is very challenging due to variations in face poses,...

Electric energy forecasting domain attracts researchers due to its key role in saving energy resources, where mainstream existing models are based on Gradient Boosting Regression, Artificial Neural Networks, Extreme Learning Machine and Support Vector Machine. These models encounter high-level of non-linearity between input data and output predicti...

Emotional state recognition of a speaker is a difficult task for machine learning algorithms which plays an important role in the field of speech emotion recognition (SER). SER plays a significant role in many real-time applications such as human behavior assessment, human robot interaction, virtual reality, and emergency centers to analyze the emo...

Autonomous vehicles rely on sophisticated hardware and software technologies for acquiring holistic awareness of their immediate surroundings. Deep learning methods have effectively equipped modern self-driving cars with high levels of such awareness. However, their application requires high-end computational hardware, which makes utilization infea...

Due to large volume and high variability of editing tools, protecting multimedia contents and ensuring their privacy and authenticity has become an increasingly important issue in cyber-physical security of industrial environments, especially industrial surveillance. The approaches authenticating images using their principle content emerge as popul...

The quality of health services provided by medical centers varies widely, and there is often a large gap between the optimal standard of services when judged based on the locality of patients (rural or urban environments). This quality gap can have serious health consequences and major implications for patient’s timely and correct treatment. These...

The advanced computational capabilities of many resource constrained devices such as smartphones have enabled various research areas including image retrieval from big data repositories for numerous IoT applications. The major challenges for image retrieval using smartphones in an IoT environment are the computational complexity and storage. To dea...

A huge number of sequence data has been generated since human genome projects starts. It’s prerequisite to examining these data. The key investigation to be accomplish is the splicing site of the genes. One of the challenging area of the bioinformatics is gene prediction. Identification of genes splicing sites prediction plays vital role in the fie...

bioinformatics is the modern application of information technology to study the living organism. In the proteins) become challenging problems which attracts many researchers toward it. Various statistical methods and machine learning techniques have been adopted by different bioinformatics researchers to predict those proteins which are attach to D...

information regarding the classification of uncharacterized membrane-proteins is more appreciated in the last decade. The degree at which the varieties of proteins are uploaded in the Pole-Genomic age and the firm process determines the function of plasma proteins in different biological experiments. However, it is necessary to have an automatic me...

Fog computing is emerging an attractive paradigm for both academics and industry alike. Fog computing holds potential for new breeds of services and user experience. However, Fog computing is still nascent and requires strong groundwork to adopt as practically feasible, cost-effective, efficient and easily deployable alternate to currently ubiquit...

Malaria is a life-threatening disease caused by parasite of genus plasmodium, which is transmitted through the bite of infected Anopheles. A rapid and accurate diagnosis of malaria is demanded for proper treatment on time. Mostly, conventional microscopy is followed for diagnosis of malaria in developing countries, where pathologist visually inspec...

This paper presents efficient optic disc segmentation algorithm which integrates the optical disc (OD) pixels information from retinal fundus images. The method is based on the homomorphic system along with the automatic seed point region growing technique which provided good results despite of variance in shape, size and uneven illumination of dif...

Facial sentiment analysis has been an enthusiastic research area for the last two decades. A fair amount of work has been done by researchers in this field due to its utility in numerous applications such as facial expression driven knowledge discovery. However, developing an accurate and efficient facial expression recognition system is still a ch...

Facial expression recognition has been an emerging and long standing research problem in last two decades. Histograms of oriented gradients (HOGs) have proven to be an effective descriptor for preserving the local information using orientation density distribution and gradient of the edge. A robust powerful approach of HOG features has been investi...

In the millions of emergency reporting calls made each year, about a quarter are non-emergencies. To avoid responding to such situations, forensic examination of the reported situation in the presence of speech as evidence has become an indispensable requirement for emergency response centers. Caller profile information like gender, age, emotional...

Content based image retrieval (CBIR) systems allow searching for visually similar images in large collections based on their contents. Visual contents are usually represented based on their properties like colors, shapes, and textures. In this paper, we propose to integrate two properties of images for constructing a discriminative and robust repre...

Many hybrid and multimodal biometric recognition techniques have been presented to provide secure and authentic systems, incorporating both soft and hard biometric schemes. This article proposes a new hybrid technique which ensures the authenticity of the user to the system, as well as monitors whether the user has passed the biometric system as a...

For many decades the facial expression analysis remain an active research area and most of the contributions have occurred in this area due to the wide range of applications like behavior analysis, to determine the mood, lie detection etc. However, to develop a robust scheme with good trade-off between high speed and accurate results is still a cha...

The face is one of the most powerful channels of nonverbal communication. Facial expression provides cues about emotion, intention, alertness, pain, personality, regulates interpersonal behavior. Automatic facial expression analysis has become an active research area that finds potential applications in areas such as more engaging human–computer in...

Recurrent neural network (RNN) and long short-term memory (LSTM) have achieved great success in processing sequential multimedia data and yielded state-of-the-art results in speech recognition, digital signal processing, video processing, and text data analysis. In this paper, we propose a novel action recognition method by processing the video dat...

Similar to a fingerprint search system, face recognition technology can assist law enforcement agencies in identifying suspects or finding missing persons. Face recognition technology lets the police detect a suspect’s face and compare it with image databases of known criminals and provides investigators with a match list of the most similar faces....

The exponential growth in the volume of digital image databases is making it increasingly difficult to retrieve relevant information from them. Efficient retrieval systems require distinctive features extracted from visually rich contents, represented semantically in a human perception-oriented manner. This paper presents an efficient framework to...

Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper...

In this paper, a novel descriptor called Weber Discrete Wavelet Transform (WDWT) is proposed. It effectively recognizes facial expressions. WDWT uses unique combination of Weber Local Descriptor (WLD) and Discrete Wavelet Transform (DWT) for efficient extraction of illumination invariant features from multi scale images. The proposed descriptor's e...

Information hiding is an active area of research where secret information is embedded in innocent-looking carriers such as images and videos for hiding its existence while maintaining their visual quality. Researchers have presented various image steganographic techniques since the last decade, focusing on payload and image quality. However, there...

Recent years have shown enthusiastic research interests in diagnostic hysteroscopy (DH), where various regions of the female reproductive system are visualized for diagnosing uterine disorders. Currently, the hysteroscopy videos produced during various sessions of patients are stored in medical libraries, which are usually browsed by medical specia...