Hameedur Rahman- PhD in Computer Science
- Professor (Associate) at Air University
Hameedur Rahman
- PhD in Computer Science
- Professor (Associate) at Air University
Associate Professor
About
84
Publications
26,821
Reads
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1,041
Citations
Introduction
Dr. Hameedur Rahman is an assistant professor at the Faculty of Computing and AI, AIR University, Islamabad-Pakistan. He has 8+ years of Industry and 6+ years of Academic experience developing applications in multi-domains. His main research areas are in Medical Disease and Cancer using Artificial Intelligence, Computer Vision, Digital Twin, Augmented/Virtual Reality, and Image processing.
Current institution
Additional affiliations
August 2021 - present
Position
- Professor (Assistant)
Description
- Teaching : Software Engineering, Practical Scripting for Games (C# & Unity3d), Game Mechanics and Computer Graphics, Multimedia Technologies. Other Duties : FYP Head, Cluster Head of Games and Multimedia & etc
February 2021 - September 2022
Position
- ASSISTANT PROFESSOR
Description
- Teaching MPhil and undergrad students, supervising 04 MPhil Research students, and also the head of final year projects (FYP). Subjects Teaching: Data Mining, Human-Computer Interaction (HCI), Digital Image Processing and Computer Vision.
January 2018 - February 2021
Position
- ASSISTANT PROFESSOR
Description
- Acting HOD of the Computer Science. Teaching Master and undergrad students, supervising undergrad students for their final year projects (FYP), and also coach them for competition throughout the world.
Education
September 2014 - January 2018
September 2010 - January 2013
LIMKOKWINGUNIVERSITYOFCREATIVETECHNOLOGY
Field of study
- SOFTWARE ENGINEERING
August 2006 - July 2010
LIMKOKWINGUNIVERSITYOFCREATIVETECHNOLOGY
Field of study
- Software Engineering with Multimedia
Publications
Publications (84)
Artificial Intelligence (AI) innovations in digital health offer unprecedented opportunities to facilitate human health and provide tools and techniques that reduce overall costs. This book discusses the use of AI to improve diagnostic accuracy, patient monitoring, the use of remote diagnostic tools, identification of life-threatening diseases, med...
This article introduces Multimodal Adaptive Patch Embedding with Vision Transformer (MAPE-ViT), a novel approach for RGB-D scene classification that effectively addresses fundamental challenges of sensor misalignment, depth noise, and object boundary preservation. Our framework integrates maximally stable extremal regions (MSER) with wavelet coeffi...
Human activity recognition (HAR) and localization are green research areas of the modern era that are being propped up by smart devices. But the data acquired from the sensors embedded in smart devices, contain plenty of noise that makes it indispensable to design robust systems for HAR and localization. In this article, a system is presented endow...
AGI-enabled drones are vital yet vulnerable systems, especially in climate monitoring and autonomous aerial missions, making cybersecurity a top priority. Dynamic, decentralized UAVs face cyber threats like DoS, spoofing, replay, and FDI attacks. This research proposes and evaluates lightweight ML-based Intrusion Detection Systems (IDS) tailored fo...
Liver cancer affects both men and women globally. Computed tomography (CT) imaging is a commonly employed modality for diagnosing and monitoring patients with hepatic malignancies.
Segmentation of the liver and tumors through CT scans represents a challenging task. The present study proposes a novel approach for segmenting liver and tumors from CT...
The increasing demand for remote healthcare solutions has driven the need for effective telerehabilitation systems to support elderly individuals recovering from chronic conditions or post-operative impairments. Existing rehabilitation methods face limitations such as restricted access to specialized care, overburdened healthcare providers, and the...
In disaster response scenarios, the formation of multi-UAV networks is a critical task. The dynamic nature of UAVs makes it difficult to employ traditional approaches. This research study presents an improved task allocation mechanism using UAV localization in disaster conditions. Due to the random movement of UAVs localization is quite a complex p...
Introduction
Recognizing human actions is crucial for allowing machines to understand and recognize human behavior, with applications spanning video based surveillance systems, human-robot collaboration, sports analysis systems, and entertainment. The immense diversity in human movement and appearance poses a significant challenge in this field, es...
In the evolving landscape of early childhood education, the integration of technology has emerged as a significant paradigm shift. This study focuses on this shift, presenting the development and evaluation of the Alphabet AR-Game—an innovative augmented reality (AR) application designed for preschool children. The game creates a dynamic learning e...
In the field of traffic surveillance systems, where effective traffic management and safety are the primary concerns, vehicle detection and tracking play an important role. Low brightness, low contrast, and noise are issues with low-light environments that result from poor lighting or insufficient exposure. In this paper, we proposed a vehicle dete...
Our book, Future of Tech Startups and Innovations in the Age of AI, mainly focuses on artificial intelligence (AI) tools, AI-based startups, AI-enabled innovations, Autonomous AI Agents (Auto-GPT), AI-based marketing startups, machine learning for organizations, AI-internet of things (IoT) for new tech companies, AI-enabled drones for agriculture i...
Introduction
Advanced traffic monitoring systems face significant challenges in vehicle detection and classification. Conventional methods often require substantial computational resources and struggle to adapt to diverse data collection methods.
Methods
This research introduces an innovative technique for classifying and recognizing vehicles in a...
Introduction: Advanced traffic monitoring systems face significant challenges in vehicle detection and classification. Conventional methods often require substantial computational resources and struggle to adapt to diverse data collection methods. Methods: This research introduces an innovative technique for classifying and recognizing vehicles in...
In computer vision and image processing, vehicle detection and tracking in complicated aerial images have become important subjects. The need for automated systems that can precisely detect and track vehicles in aerial image data
is growing due to the abundance of data coming from numerous sources, including drones and satellites. This study intro...
Introduction: Unmanned aerial vehicles (UAVs) are widely used in various computer vision applications, especially in intelligent traffic monitoring, as they are agile and simplify operations while boosting efficiency. However, automating these procedures is still a significant challenge due to the difficulty of extracting foreground (vehicle) infor...
Introduction: Unmanned aerial vehicles (UAVs) are widely used in various computer vision applications, especially in intelligent traffic monitoring, as they are agile and simplify operations while boosting efficiency. However, automating these procedures is still a significant challenge due to the difficulty of extracting foreground (vehicle) infor...
Games, particularly serious games (SGs), have long been embraced in education for their inherent engagement and
motivational qualities, especially among younger learners. In the realm of STEM education, SGs have emerged as a
technological strategy to enhance student engagement and performance. This paper addresses the growing interest in SG
impleme...
Video-based human activity recognition (HAR) is an important task in many fields, such as healthcare monitoring, video surveillance, and sports analysis. This review paper aims to give an in-depth look at the current state of the art in HAR from 2018 to 2024. This will include a discussion of the different methods and models used for extracting, re...
The liver is the largest organ of the human body with more than 500 vital functions. In recent decades, a large number of liver patients have been reported with diseases such as cirrhosis, fibrosis, or other liver disorders. There is a need for effective, early, and accurate identification of individuals suffering from such disease so that the pers...
Virtual classrooms based on the metaverse or virtual reality are useful and effective for imparting basic chemistry concepts. Interactive and immersive environments can effectively teach fundamental chemistry concepts, such as chemical bonding and formulas, thereby making these otherwise abstract and intangible ideas more accessible and understanda...
Data science approaches, which are increasingly used in virtually every sector, can be applied to the quantity of information collected from children’s interactions with augmented reality (AR) games. Data science tools can significantly improve AR game evaluation and help teachers and institutions to make evidence-based decisions. The collection, a...
A codec is the most important element of any streaming application like Netflix or YouTube, but its complexity is increasing with its advancement. The codec, High Efficiency Video Coding (HEVC), selects the intra mode out of a total of 35 intra modes using the brute-force method. Therefore, the Spiral Optimization Algorithm (SOA) is utilized in thi...
Systems must be capable of detecting and tracking autonomous vehicles for intelligent management and control of transportation. Even though several methods are used to create intelligent systems for traffic monitoring, this article explains how to detect and track vehicles using pixel labeling and particle filter algorithms. We suggested a novel te...
This paper presents an advanced approach to Human Pose Estimation (HPE) and Semantic Event Classification (SEC), emphasizing the need for sophisticated human skeleton models, context-aware feature extraction, and machine learning techniques for precise event recognition in daily life logs. HPE, crucial in applications like sports analysis and surve...
In the realm of video coding, the quest for enhanced efficiency is unending. This study introduces a novel optimization in High Efficiency Video Coding (HEVC) by refining intra-mode estimation through Ha-damard cost analysis. With the rapid evolution of codecs, real-time applications demand more than ever from the complexity of intra-mode selection...
Human activity recognition (HAR) has attracted significant attention in various fields, including healthcare, smart homes, and human-computer interaction. Accurate HAR can enhance user experience, provide critical health insights, and enable sophisticated context-aware applications. This paper presents a comprehensive system for HAR utilizing both...
In the context of 6G technology, the Internet of Everything aims to create a vast network that connects both humans and devices across multiple dimensions. The integration of smart healthcare, agriculture, transportation, and homes is incredibly appealing, as it allows people to effortlessly control their environment through touch or voice commands...
Computed tomography (CT) is used in a wide range of medical imaging diagnoses. However, the reconstruction of CT images from raw projection data is inherently complex and is subject to artifacts and noise, which compromises image quality and accuracy. In order to address these challenges, deep learning developments have the potential to improve the...
The title of our book is AIoT Innovations in Digital Health: Emerging Trends, Challenges, and Solutions. Our book mainly focuses on the techniques of green computing, big data, AI, IoT, machine learning, deep learning, fuzzy logic, ANN, and optimization techniques that can be used in digital healthcare industry. However, this proposed book offers n...
The Internet of Things (IoT) and network-enabled smart devices are crucial to the digitally interconnected society of the present day. However, the increased reliance on IoT devices increases their susceptibility to malicious activities within network traffic, posing significant challenges to cybersecurity. As a result, both system administrators a...
In virtual laboratories, various cognitive aids are used to improve students’ performance and assist them while completing experimental tasks. However, excessive use of cognitive aids in virtual laboratories can lead to a cognitive load on students which affects their performance. In this paper, we proposed the concept of adaptive aids virtual real...
Feedfoward neural network (FNN) is popular machine learning technique widely implemented for image classification, data clustering, object recognition, etc. due to its outstanding capability in processing data. Backpropagation is commonly employed as a conventional method to adjust the weights and biases of FNNs. As a gradient-based algorithm, back...
Metaheuristic search algorithms (MSAs) receive increasing popularity in recent year due to its excellent capability of solving complex real-world optimization problems without depending on gradient information. Particle swarm optimization (PSO), as one of MSAs, is widely used in optimization task due to its simple framework and quick convergence sp...
To efficiently handle the complex region, the intra modes are increased from 9 to 35 in High Efficiency Video Coding (HEVC). As a result, the encoding time is increased and makes HEVC unfit for real time applications. This article applies the firefly algorithm (FFA) in HEVC to perform fast intra mode selection. Firstly, the intra modes of HEVC are...
Medical image analysis places a significant focus on breast cancer, which poses a significant threat to women’s health and contributes to many fatalities. An early and precise diagnosis of breast cancer through digital mammograms can significantly improve the accuracy of disease detection. Computer-aided diagnosis (CAD) systems must analyze the med...
Feature selection is a crucial pre-processing step used to remove redundant information from original datasets while preserving the accuracy and processing time of classifier. The feasibility of using metaheuristic search algorithms (MSAs) such as Flow Directional Algorithm (FDA) to solve feature selection problems is one of the active research top...
Abstract A vehicular ad‐hoc network (VANET) is derived from a mobile ad‐hoc network that is a part of less infrastructure network design. Vehicular communication in VANET can be achieved using vehicle‐to‐infrastructure (V2I) and vehicle‐to‐vehicle (V2V) communication. A vehicle communicates with other vehicles through onboard units while communicat...
World’s second most occurring cancer is breast cancer. Prediction of disease is one of the most challenging tasks and there are many factors that effect this type of diagnosis like the ability of visual perception. This paper proposed a Convolutional Neural Network (CNN) based proper method for analyzing the earliest signs of breast cancer with the...
With the versatility and exponential growth of IoT solutions, the probability of being attacked has increased. Resource constraint IoT devices raised a challenge for the security handler to track logs of different variety of attacks generated on them while performing the forensic analysis. Commonly forensic analysis is performed on the devices that...
Sentiment Analysis (SA) is often referred to as opinion mining. It is defined as the extraction, identification, or characterization of the sentiment from text. Generally, the sentiment of a textual document is classified into binary classes i.e., positive and negative. However, fine-grained classification provides a better insight into the sentime...
Many real-world engineering problems such as machining processes are multi-objective optimization problems (MOPs) because multiple performance characteristics are considered to satisfy their contradictory goals. An improved multi objective teaching-learning-based optimization with refined knowledge sharing mechanisms (IMTLBO-RKSM) is proposed to ta...
Augmented reality (AR) technology is playing an important role in the preschool education. AR provides cost-effective learning systems which improve the attention skills of preschool children. In AR technology, the marker is used as an open-source computer tracking object to create AR applications that overlay virtual imagery on the physical world....
Traffic speed prediction is a vital part of the intelligent transportation system (ITS). Predicting accurate traffic speed is becoming an important and challenging task with the rapid development of deep learning and increasing traffic data size. In this study, we present a deep-learning-based architecture for network-wide traffic speed prediction....
Traffic speed prediction is a vital part of the intelligent transportation system (ITS). Predicting accurate traffic speed is becoming an important and challenging task with the rapid development of deep learning and increasing traffic data size. In this study, we present a deep-learning-based architecture for network-wide traffic speed prediction....
The brute-force behaviour of High Efficiency Video Coding (HEVC) is the biggest hurdle in the communication of multimedia content. Therefore, two novel methods will be presented here to expedite the intra mode decision process of HEVC. In the first algorithm, the feasibility of Histogram of Oriented Gradients (HOG) for early intra mode decision is...
According to the most recent estimates from global cancer statistics for 2020, liver cancer is the ninth most common cancer in women. Segmenting the liver is difficult, and segmenting the tumor from the liver adds some difficulty. After a sample of liver tissue is taken, imaging tests, such as magnetic resonance imaging (MRI), computer tomography (...
Numerous particle swarm optimization (PSO) variants were proposed in past decades to tackle different types optimization problems more robustly. Nevertheless, the imbalance of explorative and exploitative search behaviors remains as an ongoing research challenge that can restrict the performance of PSO. In this paper, a new variant known as PSO wit...
Numerous particle swarm optimization (PSO) variants were proposed in past decades to tackle different types optimization problems more robustly. Nevertheless, the imbalance of explorative and exploitative search behaviors remains as an on-going research challenge that can restrict the performance of PSO. In this paper, a new variant known as PSO wi...
Skin lesion segmentation plays a critical role in the precise and early detection of skin cancer via recent frameworks. The prerequisite for any computer-aided skin cancer diagnosis system is the accurate segmentation of skin malignancy. To achieve this, a specialized skin image analysis technique must be used for the separation of cancerous parts...
Early childhood learning is an important concern for the concept building of children. Students have been taught with traditional methods from the beginning. However, these methods lack kids’ attention. Application of Augmented Reality (AR) in a traditional way of teaching can help students in better engagement and better learning. In this research...
Deforestation is the long-term or permanent conversion of forest land to other uses, such as agriculture, mining, and urban development. As a result, deforestation has catastrophic consequences for the environment, including the loss of biodiversity, disruption of clean water supplies, and the acceleration of climate change. According to statistics...
Comprehension algorithms like High Efficiency Video Coding (HEVC) facilitates fast and efficient handling of multimedia contents. Such algorithms involve various computation modules that help to reduce the size of content but preserve the same subjective viewing quality. However, the brute-force behavior of HEVC is the biggest hurdle in the communi...
Security has recently been given the highest priority with the rise in the number of antisocial activations taking place. To continuously track individuals and their interactions, CCTVs have been built in several ways. Every person is recorded on an image on average 30 times a day in a developed world with a community of 1.6 billion. The resolution...
Fifth-generation (5G) has been classified as an ultra-reliable low latency communication (URLLC) by International Telecommunication Union (ITU) to meet the varied market and industrial needs. Future cellular networks aim to fulfil the requirements to achieve seamless Ultra-Reliable & Low Latency Communication (URLLC) in delay sensitive applications...
Image processing has an important factor called image Segmentation which is very important and initial step in medical image processing. In this process, image is partition according to distinct region. Processing of MRI scan image is the part of medical field. In this project, we use the patient's MRI scan image to detect the Brain tumor using GUI...
Verification is a main concern with computer-based systems. Face recognition is commonly often used in many applications like protection device and door lock. Universities, Colleges, schools and library attendance are compulsory for every student. Current attendance approach is lecturer calling the roll number and name of the student and then marki...
Detection of skin cancer disease is very important in early stage. In these days, Skin cancer is most dangerous, a type of man-made cancers. Skin cancer occurs in various forms such as melanoma, basal cells of which, the most impredicatable is Melanoma. Early cancer diagnosis can be effective in treating it in the diagnosis of Medical Picture. In t...
Breast tumor is the main cause for death amongst women. The aim of this project is plan and contrivance a MATLAB created image processing structure to extract features of breast cancer images in order to classify breast cancer through neural network from mammogram x-rays image (MXI). Breast Cancer (BC) happens several of the most common reasons of...
Lung cancer is the result of cells that develop widely in one or both of the lungs. Lung cancer is diagnosed in two ways non-small cell lung cancer and small cell lung cancer. Too late, lung cancer has been the main cause of death worldwide. If detected successfully in the early stages lung cancer allows for many treatment options, decrease the ris...
Internet of thing IoT introduced various opportunities for novel applications, which are utilized in agriculture and many more. In the world, Chilli is very significant plant due to its huge ingesting. Chilli has many medicinal properties and using in many foods in Pakistan. Anthracnose produced through Colletotrichum spp. consumes stayed one of th...
![FIGURE 1. Top 10 languages in the Internet in millions of users.[8]](profile/Nurul-Kamaruddin/publication/322688865/figure/fig1/AS:586487762542592@1516840987734/Top-10-languages-in-the-Internet-in-millions-of-users8_Q320.jpg)
![FIGURE 6. Watermark generation using word context. [25]](profile/Nurul-Kamaruddin/publication/322688865/figure/fig3/AS:586487762522112@1516840987855/Watermark-generation-using-word-context-25_Q320.jpg)
During the recent years, the issue of preserving the integrity of digital text has become a focus of interest in the transmission of online content on the Internet. Watermarking has a useful tool in the protection of digital text content as it solves the problem of tampering, duplicating, unauthorized access and security breaches. The rapid develop...
Breast Cancer patients who require breast biopsy has increased over the past years. Augmented Reality guided core biopsy of breast has become the method of choice for researchers. However, this cancer visualization has limitations to the extent of superimposing the 3D imaging data only. In this paper, we are introducing an Augmented Reality visuali...
Breast cancer patients who require breast biopsy have increased over the past years and Stereotactic Biopsy uses series of images to carefully position the imaging equipment and target the area of concern. However, it has the constraint of accurate 3D Tumor visualization. An Augmented Reality (AR) Guidance Biopsy system of breast has become the met...
Continuous tracking in Augmented Reality (AR) applications is essential for registering and augmenting the digital content on top of the real world. However, tracking on handheld devices such as PDAs or mobile phones enforces many restrictions and challenges in the form of efficiency and robustness which are the standard performance measures of tra...
An AMP is a project where the goal is to enhance the experience of locating friends and family by using GPS and standard web technology. This has lead to a design consisting of three parts: a mobile client, a repository, a web client, and a map service. The mobile client, which consists of a mobile phone and a GPS receiver, can be used to find the...
WBPS is a project where the goal is to enhance the experience of locating friends and family by using GPS and standard web technology. This has lead to a design consisting of three parts: a mobile client, a repository, a web client, and a map service. The mobile client, which consists of a mobile phone and a GPS receiver, can be used to find the lo...
Questions
Question (1)
Respected all Professors,
I would like to know what could possibly be the best book on research methodology for emerging technologies, or if anyone can help me determine what should be the least learning outcome for the student after studying the research methodology in the computer science domain. From what I've seen, a lot of students don't learn much in the research methodology class.
I would need some good suggestions and help.
