Khan Muhammad

Khan Muhammad
Sungkyunkwan University | SKKU · Department of Applied Artificial Intelligence

BCS (Hons), PhD (Digital Contents)

About

261
Publications
151,778
Reads
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10,066
Citations
Introduction
I am currently an Assistant Professor (T.T.G) and Director of Visual Analytics for Knowledge (VIS2KNOW) Lab at the Department of Applied AI, Sungkyunkwan University, South Korea. My research areas are information security, AI, video summarization, visual analytics, fire/smoke scene analysis, big data, and Io(M)T. Contact me if you are interested in research collaboration in the relevant areas of our joint interest: khan.muhammad.icp[@]gmail.com, khan.muhammad[@]ieee.org Skype/WeChat: khan3768
Additional affiliations
February 2022 - present
Sungkyunkwan University
Position
  • Professor (Assistant)
March 2019 - February 2022
Sejong University
Position
  • Professor (Assistant)
March 2015 - February 2019
Sejong University
Position
  • Research Associate (PhD Fellow)
Education
March 2015 - February 2019
Sejong University
Field of study
  • Digital Contents
November 2010 - August 2014
Islamia College Peshawar
Field of study
  • Computer Science
September 2008 - August 2010
Islamia College Peshawar
Field of study
  • Computer Science

Publications

Publications (261)
Article
Smoke detection in foggy surveillance environments is a challenging task and plays a key role in disaster management for industrial systems. The current smoke detection methods are applicable to only normal surveillance videos, providing unsatisfactory results for video streams captured from foggy environments, due to challenges related to clutter...
Article
Video Summarization (VS) has attracted intense attention recently due to its enormous applications in various computer vision domains such as video retrieval, indexing, and browsing. Traditional VS researches mostly target at the effectiveness of VS algorithms by introducing high quality of features and clusters for selecting representative visual...
Article
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade recognition is a challenging problem for radiologists in health monitoring and automated diagnosis. Recently, numerous methods based on deep learning have been presented in the literature for brain tumor classification (BTC) in order to assist radiologists for a b...
Article
Full-text available
Advances in information and signal processing technologies have a significant impact on autonomous driving (AD), improving driving safety while minimizing the efforts of human drivers with the help of advanced artificial intelligence (AI) techniques. Recently, deep learning (DL) approaches have solved several real-world problems of complex nature....
Article
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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....
Article
Short-term electrical energy load forecasting is one of the most significant problems associated with energy management for smart grids, which aims to optimize the operational strategies of buildings. Electricity forecasting models are considered a key aspect of the provision of better electricity management and reductions in energy consumption. Th...
Article
Recent advancements in intelligent surveillance systems for video analysis have been a topic of great interest in the research community due to the vast number of applications to monitor humans’ activities. The growing demand for these systems aims towards automatic violence detection (VD) systems enhancing and comforting human lives through artifi...
Article
Full-text available
The massive number of research articles on the Web makes it troublesome for researchers to identify related works that could meet their preferences and interests. Consequently, various network representation learning-based models have been proposed to produce citation recommendations. Nevertheless, these models do not exploit semantic relations and...
Article
The accuracy of WiFi fingerprint-based localization is related to the number of reference points, generally, to obtain better positioning accuracy, enough samples must be collected, which will inevitably lead to a huge sampling workload. Thus, it will be of great significance to design an algorithm using sparse samples to achieve positioning accura...
Article
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...
Article
During the last decades, recommender systems are becoming quite popular since they provide great assistance to users on social networks and library websites. Unfortunately, the large volume of data combined with sparsity makes personalization a difficult task. In this regard, several models were introduced in the literature that suffers from the co...
Article
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Open-source intelligence (OSINT) tools are used for gathering information using different publicly available sources. With the rapid advancement in information technology and excessive use of social media in our daily lives, more public information sources are available than ever before. The access to public information from different sources can b...
Article
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In this paper, we propose an adaptive encryption scheme for color images using Multiple Distinct Chaotic Maps (MDCM) and DNA computing. We have chosen three distinct chaotic maps, including a 2D-Henon map, a Tent map, and a Logistic map, to separately encrypt the red, green, and blue channels of the original image. The proposed scheme adaptively mo...
Article
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The ant colony optimization algorithm is a classical swarm intelligence algorithm, but it cannot be used for continuous class optimization problems. A continuous ant colony optimization algorithm (ACOR) is proposed to overcome this difficulty. Still, some problems exist, such as quickly falling into local optimum, slow convergence speed, and low co...
Article
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In the Cooperative Intelligent Transportation System (C-ITS) paradigm, vehicles could communicate with roadside units to augment their traffic knowledge. Smart roadside units could provide second-order information (e.g., vehicle count) from raw first-order data (e.g., visual feed, point clouds), and this ``smart'' feature is usually provided using...
Article
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Wireless capsule endoscopy (WCE), the most efficient technology, is used in the endoscopic department for the examination of gastrointestinal (GI) diseases such as a poly and ulcer. WCE generates thousands of frames for a single patient's procedure, and the manual examination is time-consuming and exhausting. In the WCE frames, computerized techniq...
Article
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Nowadays, Blockchain application is rapidly developing in the banking, finance, and capital market. Blockchain application is a leading innovation in the finance industry to avoid fraud in transactions and ensure quick and secure trade. It will be an interconnected global financial system to reduce the risk and manage the financial data. The global...
Article
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User counterparts, such as user attributes in social networks and their interests, are the key steps towards more natural Human-Computer Interaction (HCI). In addition, the users' attributes and social structures help to understand the complex interactions in HCI. Most previous studies have been based on supervised learning to improve the performan...
Article
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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...
Poster
Full-text available
We welcome original theoretical, empirical, and experimental manuscripts (Word, LaTeX, etc.) dealing with the book's topics (7,000-10,000 words). All chapters submitted for publication in this book will be blind reviewed. The submission will be made through email @: irfansiddiqui1986@gmail.com
Article
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One of the fascinating aspects of sports rivalry is that anything can happen. The significant difficulty is that computer-aided systems must address how to record and analyze many game events, and fractal AI plays an essential role in dealing with complex structures, allowing effective solutions. In table tennis, we primarily concentrate on two iss...
Article
From early 2020, a novel coronavirus disease pneumonia has shown a global “pandemic” trend at an extremely fast speed. Due to the magnitude of its harm, it has become a major global public health event. In the face of dramatic increase in the number of patients with COVID-19, the need for quick diagnosis of suspected cases has become particularly c...
Preprint
Full-text available
Advancements in smart vehicle design have enabled the creation of Internet of Vehicle (IoV) technologies that can utilize the information provided by various sensors and wireless communication to perform complex functionality. Many of these functionalities rely on high computational power and low latency. Mobile Edge Computing (MEC) technologies ha...
Article
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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...
Article
Person reidentification (P-Reid) is an emerging research domain in the field of information retrieval that has gained exponential growth due to its wide range of applications in pedestrian tracking and crime prevention. The primary goal of P-Reid is to recognize a person based on previous appearance in multiview surveillance videos. The mainstream...
Article
Computer vision has always been a hot field of research by contemporary scholars due to its wide range of applications. As an important branch of this field, visual monitoring technology has shown superior vitality in the actual monitoring environment of the Internet of Things (IoT). However, when the monitoring environment is complex, once the tar...
Article
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In healthcare, the human body is a controlled input-output system, which generates different observations with the variations of external interventions. The intervention acts as the input, and the output is the phenotype observation that reflects the latent health state of the body system. The objective of healthcare is to determine effective inter...
Article
Rapid developments in deep learning (DL) and the Internet-of-Things (IoT) have enabled vision-based systems to efficiently detect fires at their early stage and avoid massive disasters. Implementing such IoT-driven fire detection systems can significantly reduce the corresponding ecological, social, and economic destruction; they can also provide s...
Article
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Convolutional Neural Network (CNN) based approaches are popular for various image/video related tasks due to their state-of-the-art performance. However, for problems like object detection and segmentation, CNNs still suffer from objects with arbitrary shapes or sizes, occlusions, and varying viewpoints. This problem makes it mostly unsuitable for...
Article
Dynamic CT angiography derived from CT perfusion data can obviate a separate coronary CT angiography and the use of ionizing radiation and contrast agent, thereby enhancing patient safety. However, the image quality of dynamic CT angiography is inferior to standard CT angiography images in many studies. This paper proposes an explainable generative...
Article
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In the Industry 4.0 era, the visualization and real-time automatic monitoring of smart cities supported by the Internet of Things is becoming increasingly important. The use of filtering algorithms in smart city monitoring is a feasible method for this purpose. However, maintaining fast and accurate monitoring in complex surveillance environments w...
Article
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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...
Article
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Anterior Chamber Angle (ACA) assessment plays an important role for the diagnosis of glaucoma. Most of the existing techniques relied on Anterior Segment Optical Coherence Tomography (AS-OCT) or Swept Source Optical Coherence Tomography (SS-OCT). We proposed a system for 360° overview of iridocorneal angle of anterior chamber (ICAAC) via Ultrasound...
Article
In the last few years, visual sensors are deployed almost everywhere, generating a massive amount of surveillance video data in smart cities that can be inspected intelligently to recognize anomalous events. In this work, we present an efficient and robust framework to recognize anomalies from surveillance Big Video Data (BVD) using Artificial Inte...
Article
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In the recent pandemic, accurate and rapid testing of patients remained a critical task in the diagnosis and control of COVID-19 disease spread in the healthcare industry. Because of the sudden increase in cases, most countries have faced scarcity and a low rate of testing. Chest X-rays have been shown in the literature to be a potential source of...
Article
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With the rapid development of information technology, the conception of smart healthcare has progressively come to the fore. Smart healthcare utilizes next-generation technologies, such as artificial intelligence, the internet of things (IoT), big data and cloud computing to transform intelligently the existing medical system - making it more effic...
Article
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Analyzing surveillance videos is mandatory for the public and industrial security. Overwhelming growth in computer vision fields has been made to automate the surveillance system in terms of human activity recognition such as behavior analysis, Violence Detection (VD), etc. However, it is challenging to detect and analyze the violent scenes intelli...
Article
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...
Poster
Full-text available
Dear Colleagues, We are in the process of coming up with a volume titled Computer Intelligence against Pandemics - Tools and Methods to face new Strains of Covid-19 to be published by De Gruyter, Germany in 2022. This book introduces the most recent research and innovative developments regarding the new strains of COVID-19. At this point, computat...
Article
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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...
Article
In this work, the effectiveness of the deep learning model is applied for one-dimensional data when converted to images. This work is based on the effective conversion of one-dimensional data to images and designing a stacked ensemble deep learning model that can increase the performance of classification accuracy in comparison to single models. Br...
Article
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In recent times,COVID-19, has a great impact on the healthcare sector and results in a wide range of respiratory illnesses. It is a type of Ribonucleic acid (RNA) virus, which affects humans as well as animals. Though several artificial intelligence-based COVID-19 diagnosis models have been presented in the literature, most of the works have not fo...
Article
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The universe, with its fractal structure patterns, includes infinite array of elements interacting in complex systems, while manifesting adaptability, self-organization and sensitivity to the external environment. A fractal system is also a nonlinear, complex and interactive system capable of adapting to a vague environment where Fractional Calculu...
Article
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Urban surveillance, of which airborne urban surveillance is a vital constituent, provides situational awareness (SA) and timely response to emergencies. The significance and scope of urban surveillance has increased manyfold in recent years due to the proliferation of unmanned aerial vehicles (UAVs), Internet of things (IoTs), and multitude of sens...
Article
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This overview gravitates on research achievements that have recently emerged from the confluence between Big Data technologies and bio-inspired computation. A manifold of reasons can be identified for the profitable synergy between these two paradigms, all rooted on the adaptability, intelligence and robustness that biologically inspired principles...
Article
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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...
Article
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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...
Article
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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...
Article
Vehicle detection and tracking play an important role in autonomous vehicles and intelligent transportation systems. Adverse weather conditions such as the presence of heavy snow, fog, rain, dust or sandstorm situations are dangerous restrictions on camera's function by reducing visibility, affecting driving safety. Indeed, these restrictions impac...