Ahmed Iqbal

COMSATS University Islamabad (CUI)

Accurate breast lesion segmentation is a great help in the initial stage of breast cancer treatment planning. Ultrasound is considered the safe and cheapest method for the breast screening process. However, ultrasound images inherently contain speckle noise, unclear boundaries, and complex shapes, making it more challenging for automatic segmentati...

Breast cancer is considered the most commonly diagnosed cancer globally and falls second to lung cancer. For the early detection of breast tumors in women, breast cancer analysis using Ultrasound, Mammography, and MRI modalities is used as an initial screening process. Due to the random variation, irregular shapes, and blurred boundaries of tumor r...

Tuberculosis still significantly impacts the world's population, with more than 10 million people getting sick each year. Researchers have focused on developing computer-aided diagnosis (CAD) technology based on X-ray imaging to support the identification of tuberculosis, and deep learning is a popular and efficient method. However, deep learning-b...

Recent advancements with deep generative models have proven significant potential in the task of image synthesis, detection, segmentation, and classification. Segmenting the medical images is considered a primary challenge in the biomedical imaging field. There have been various GANs-based models proposed in the literature to resolve medical segmen...

Early diagnosis of tuberculosis (TB) is an essential and challenging task to prevent disease, decrease mortality risk, and stop transmission to other people. The chest X-ray (CXR) is the top choice for lung disease screening in clinics because it is cost-effective and easily accessible in most countries. However, manual screening of CXR images is a...

Automatic multimodal image segmentation is considered a challenging research area in the biomedical field. U-shaped models have led to an enormous breakthrough in a large domain of medical image segmentation in recentyears. The receptive field plays an essential role in convolutionalneural networks because too small a receptive field limits context...

Production of high-quality software at lower cost has always been the main concern of developers. However, due to exponential increases in size and complexity, the development of qualitative software with lower costs is almost impossible. This issue can be resolved by identifying defects at the early stages of the development lifecycle. As a signif...

Extreme programming (XP) is one of the widely used software process model for the development of small scale projects from agile family. XP is widely accepted by software industry due to various features it provides such as: handling frequent changing requirements, customer satisfaction, rapid feedback, iterative structure, team collaboration, and...

Extreme programming (XP) is one of the widely used software process model for the development of small scale projects from agile family. XP is widely accepted by software industry due to various features it provides such as: handling frequent changing requirements, customer satisfaction, rapid feedback, iterative structure, team collaboration, and...

Selection of an appropriate software development process model is the key aspect, which leads to the development of high-quality product within scheduled time. The selection of development model depends upon various aspects, related to the project, such as: size, complexity, and scheduled time. Agile family has been satisfying the software industry...

Testing is considered as one of the expensive activities in software development process. Fixing the defects during testing process can increase the cost as well as the completion time of the project. Cost of testing process can be reduced by identifying the defective modules during the development (before testing) stage. This process is known as "...

Prediction of defect prone software modules is now considered as an important activity of software quality assurance. This approach uses the software metrics to predict whether the developed module is defective or not. This research presents MLP based ensemble classification framework to predict the defect prone software modules. The framework pred...

Production of high quality software at lower cost can be possible by detecting defect prone software modules before the testing process. With this approach, less time and resources are required to produce a high quality software as only those modules are thoroughly tested which are predicted as defective. This paper presents a classification framew...

Testing is one of the crucial activities of software development life cycle which ensures the delivery of high quality product. As software testing consumes significant amount of resources so, if, instead of all software modules, only those are thoroughly tested which are likely to be defective then a high quality software can be delivered at lower...

Predicting the defects at early stage of software development life cycle can improve the quality of end product at lower cost. Machine learning techniques have been proved to be an effective way for software defect prediction however an imbalance dataset of software defects is the main issue of lower and biased performance of classifiers. This issu...

The exponent increase in the use of online information systems triggered the demand of secure networks so that any intrusion can be detected and aborted. Intrusion detection is considered as one of the emerging research areas now days. This paper presents a machine learning based classification framework to detect the Denial of Service (DoS) attack...

Software defect prediction is one of the emerging research areas of software engineering. The prediction of defects at early stage of development process can produce high quality software at lower cost. This research contributes by presenting a feature selection based ensemble classification framework which consists of four stages: 1) Dataset selec...

Defect prediction at early stages of software development life cycle is a crucial activity of quality assurance process and has been broadly studied in the last two decades. The early prediction of defective modules in developing software can help the development team to utilize the available resources efficiently and effectively to deliver high qu...

Network security is an essential element in the day-today IT operations of nearly every organization in business. Securing a computer network means considering the threats and vulnerabilities and arrange the countermeasures. Network security threats are increasing rapidly and making wireless network and internet services unreliable and insecure. In...

Empirical analysis evaluates the proposed system via practical experience and reveals its pros and cons. Such type of evaluation is one of the widely used validation approach in software engineering. Conventional software process models were performed well till mid 1990s but then gradually were replaced by agile methodologies. This happened due to...