Muhammad Khusairi Osman
YOU?
Author Swipe
View article: Genetic algorithm-adapted activation function optimization of deep learning framework for breast mass cancer classification in mammogram images
Genetic algorithm-adapted activation function optimization of deep learning framework for breast mass cancer classification in mammogram images Open
The convolutional neural network (CNN) has been explored for mammogram cancer classification to aid radiologists. CNNs require multiple convolution and non-linearity repetitions to learn data sparsity, but deeper networks often face the va…
View article: Acute Lymphoblastic Leukemia Blood Cell Image Classification Using Convolutional Neural Network
Acute Lymphoblastic Leukemia Blood Cell Image Classification Using Convolutional Neural Network Open
Due to the disease's late discovery, the number of new cases of Acute lymphoblastic leukemia (ALL) is rising along with its high fatality rates. However, the traditional method of diagnosing Acute lymphoblastic leukemia often involves mult…
View article: Better Network Optimization Through Batch Normalization in Left Ventricle Chamber Classification
Better Network Optimization Through Batch Normalization in Left Ventricle Chamber Classification Open
Convolutional neural networks (CNNs) have emerged as a prominent deep learning technique for medical image classification. This study investigated the impact of batch normalization layer placement on the performance of the CNNs model in cl…
View article: Deep Ensemble approach for Enhancing Brain Tumor Segmentation in Resource-Limited Settings
Deep Ensemble approach for Enhancing Brain Tumor Segmentation in Resource-Limited Settings Open
Segmentation of brain tumors is a critical step in treatment planning, yet manual segmentation is both time-consuming and subjective, relying heavily on the expertise of radiologists. In Sub-Saharan Africa, this challenge is magnified by o…
View article: 2TSS: Two-Tier Semantic Segmentation Framework With Enhancement for Hotspot Detection of Solar Photovoltaic Thermal Images
2TSS: Two-Tier Semantic Segmentation Framework With Enhancement for Hotspot Detection of Solar Photovoltaic Thermal Images Open
Recently, intelligence-based hotspot detection has been widely used in solar photovoltaic (PV) image applications. However, the semantic segmentation approach has limitations in terms of accuracy, particularly for hotspot thermal images. T…
View article: A Review on Time Series Data Augmentation Techniques for Deep Learning
A Review on Time Series Data Augmentation Techniques for Deep Learning Open
Recently, deep artificial neural networks have gained huge attention in pattern recognition and classification. The classification models that are trained with insufficiently large datasets can contribute to degradation of generalization a…
View article: Deep Learning-Driven Thermal Imaging Hotspot Detection in Solar Photovoltaic Arrays Using YOLOv10
Deep Learning-Driven Thermal Imaging Hotspot Detection in Solar Photovoltaic Arrays Using YOLOv10 Open
The effective management of solar photovoltaic (PV) arrays is vital to maximising energy generation and ensuring long-term performance reliability. The presence of faults, or partial shading, can give rise to hotspots in PV arrays, making …
View article: Comparing CNN-based Architectures for Dysgraphia Handwriting Classification Performance
Comparing CNN-based Architectures for Dysgraphia Handwriting Classification Performance Open
Deep learning algorithms are increasingly being used to diagnose dysgraphia by concentrating on the issue of uneven handwriting characteristics, which is common among children in the early stage of basic learning of reading and writing ski…
View article: Development of potential dysgraphia handwriting dataset
Development of potential dysgraphia handwriting dataset Open
This report presents a dataset of offline handwriting samples among Malaysian schoolchildren with potential dysgraphia. The images contained Malay sentences written by primary school students and children under intervention by the Malaysia…
View article: Environmental Lighting towards Growth Effect Monitoring System of Plant Factory using ANN
Environmental Lighting towards Growth Effect Monitoring System of Plant Factory using ANN Open
Malaysia is currently driven to become another most developed country in the world. Among other priority sector is Food Sustainability. Along the process, our vegetable supply-demand keeps increasing by year. Compared to traditional system…
View article: Urban Farming Growth Monitoring System Using Artificial Neural Network (ANN) and Internet of Things (IOT)
Urban Farming Growth Monitoring System Using Artificial Neural Network (ANN) and Internet of Things (IOT) Open
As an introduction to this project, the growth-related traits, such as above-ground biomass and leaf area, are critical indicators to characterize the growth of indoor lettuce plants. Currently, non-destructive methods for estimating growt…
View article: Automated DeepLabV3+ based model for left ventricle segmentation on short-axis late gadolinium enhancement-magnetic cardiac resonance imaging images
Automated DeepLabV3+ based model for left ventricle segmentation on short-axis late gadolinium enhancement-magnetic cardiac resonance imaging images Open
Accurate segmentation of myocardial scar tissue on late gadolinium enhancement-magnetic cardiac resonance imaging (LGE-CMR) is exceptionally vital for clinical applications, enabling precise diagnosis and effective treatment of various car…
View article: Enhancing lung lesion localization in CT-scans: a novel approach using FE_CXY and statistical analysis
Enhancing lung lesion localization in CT-scans: a novel approach using FE_CXY and statistical analysis Open
Intelligence algorithm systems rely on a large dataset to effectively extract significant features that can recognize patterns for classification purposes and extensively utilized to assist the physicians in diagnosis of lung cancer. Extra…
View article: Adaptive fuzzy weighted median filter for microcalcifications detection in digital breast tomosynthesis images
Adaptive fuzzy weighted median filter for microcalcifications detection in digital breast tomosynthesis images Open
Breast cancer is a global leading cause of female mortality. Digital breast tomosynthesis (DBT) is pivotal for early breast cancer detection, with microcalcifications serving as crucial indicators. However, the movement of the DBT machine …
View article: Design of Buck Converter Based on Maximum Power Point Tracking for Photovoltaic Applications
Design of Buck Converter Based on Maximum Power Point Tracking for Photovoltaic Applications Open
e MPPT converter ensures that the PV system operates at the maximum power point, which is the point where the solar panels can generate the most power. This is done by adjusting the voltage of the output. The converter uses a DC-DC convers…
View article: Convolutional Neural Network for Transmission Line Fault Diagnosis Based on Signal Segmentation Approach
Convolutional Neural Network for Transmission Line Fault Diagnosis Based on Signal Segmentation Approach Open
Convolutional Neural Network (CNN) is a Deep Learning algorithm that can take in an input signal, assign importance (learnable weights and biases) to various aspects of the signals and distinguish between them. The CNN algorithm trains a s…
View article: Image segmentation and feature extraction method for lung lesion detection in computed tomography images
Image segmentation and feature extraction method for lung lesion detection in computed tomography images Open
Lung cancer is a form of cancer that causes uncontrollable cell growth in the lungs. Patients with lung cancer frequently miss a treatment, face higher health care costs, and get the worst outcomes. The detection of the existence of lung c…
View article: Development of Stride Detection System for Helping Stroke Walking Training
Development of Stride Detection System for Helping Stroke Walking Training Open
Walking is a popular post-stroke rehabilitation exercise for patients. Stroke walking training is a sort of physical therapy that aims to help people who have had a stroke improve their walking ability. The goal of this research is to clas…
View article: LAPLACIAN-BASED BLUR DETECTION ALGORITHM FOR DIGITAL BREAST TOMOSYNTHESIS IMAGES IN IMPROVING BREAST CANCER DETECTION
LAPLACIAN-BASED BLUR DETECTION ALGORITHM FOR DIGITAL BREAST TOMOSYNTHESIS IMAGES IN IMPROVING BREAST CANCER DETECTION Open
The most challenging aspect of working with digital images captured in an uncontrolled environment is to determine whether the image is of sufficient quality to be studied further. One of the most frequent reasons for a decrease in the qua…
View article: FUZZY WEIGHTED MEDIAN FILTER WITH UNSHARP MASKING FOR ENHANCEMENT OF DBT IMAGES IN BREAST CANCER DETECTION
FUZZY WEIGHTED MEDIAN FILTER WITH UNSHARP MASKING FOR ENHANCEMENT OF DBT IMAGES IN BREAST CANCER DETECTION Open
Breast cancer survival rates can be increased by providing early treatment to patients; thereby, microcalcification detection is critical because microcalcifications are an early sign of breast cancer. The visibility of microcalcifications…
View article: Characterising Colour Feature Descriptors for Ficus carica L. Ripeness Classification Based on Artificial Neural Network (ANN)
Characterising Colour Feature Descriptors for Ficus carica L. Ripeness Classification Based on Artificial Neural Network (ANN) Open
Excessive feature dimensions impact the effectiveness of machine learning, computationally expensive and the analysis of feature correlations in the engineering area. This paper uses the colour descriptor to get the most optimal feature to…
View article: GEOMETRICAL FEATURE OF LUNG LESION IDENTIFICATION USING COMPUTED TOMOGRAPHY SCAN IMAGES
GEOMETRICAL FEATURE OF LUNG LESION IDENTIFICATION USING COMPUTED TOMOGRAPHY SCAN IMAGES Open
Lung lesion identification is an important aspect of an early lung cancer diagnosis. Early identification of lung cancer may assist physicians in treating patients. This paper uses computed tomography scan images to present a lung lesion i…
View article: Enhancement Technique Based on the Breast Density Level for Mammogram for Computer-Aided Diagnosis
Enhancement Technique Based on the Breast Density Level for Mammogram for Computer-Aided Diagnosis Open
Mass detection in mammograms has a limited approach to the presence of a mass in overlapping denser fibroglandular breast regions. In addition, various breast density levels could decrease the learning system’s ability to extract sufficien…
View article: Classification of Left Ventricle and Non- Left Ventricle Segment for Cardiac Assessment Using Deep Convolutional Neural Network
Classification of Left Ventricle and Non- Left Ventricle Segment for Cardiac Assessment Using Deep Convolutional Neural Network Open
In large-scale medical imaging, selecting the best image to extract relevant imaging biomarkers for image assessment is crucial.Segmentation of the left ventricle (LV) and myocardium are performed in computer-aided analysis usually at shor…
View article: Deep Learning Approach for Blur Detection of Digital Breast Tomosynthesis Images
Deep Learning Approach for Blur Detection of Digital Breast Tomosynthesis Images Open
Image quality is critical in domains such as computer vision, image processing, and pattern recognition.One of the areas of image processing where image quality is critical is image restoration.In the field of medical imaging, blur detecti…