Mohd Yusoff Mashor, Prof. Dr.
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This page provides access to research works by Prof. Dr. Mohd Yusoff Mashor, currently a Professor of School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP).
Skills and Expertise: Machine Learning, Image Processing, Pattern Recognition Classification, Signal Processing, Neural Networks and Artificial Intelligence, Control Theory, Computer Vision, Signal, Image and Video Processing, Feature Extraction Algorithms,Computational Intelligence, MATLAB, Clustering, Pattern Classification, Artificial Intelligence, Object Recognition, Applied Artificial Intelligence, Electronic Engineering, Artificial Neural Networks, Image Data Analysis, Signal Analysis System Identification, Control Systems Engineering, Computer Engineering, Fuzzy Clustering, Controller Design Fuzzy Logic, Adaptive Control, Clustering Algorithms, Cervical Cancer, Fuzzy Control Intelligent Systems, Fuzzy Logic Control, Fuzzy Systems and Intelligent Control.
Recent Submissions
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An Automated Segmentation and Counting of Ki67 Cells in Meningioma Using K-Means Clustering Technique
(IOP Publishing, 2019)Meningioma is a type of primary brain tumours. The meningiomas account for about one-third of all primary brain tumours. Image segmentation plays an important role in image analysis, especially detecting the tumours or ... -
Classification of Acute Leukemia Based on Multilayer Perceptron
(IOP Publishing, 2019)In general, various artificial neural network have been applied in many areas such as modelling, pattern recognition, signal processing, diagnostic and prognostic. In this paper, artificial neural network are used to detect ... -
Segmentation of Relevant Region in Breast Histopathology Images using FCM with Guided Initialization
(IOP Publishing, 2019)This study proposes a modified initialization approach for the conventional FCM, namely FCM with guided initialization. The FCM with guided initialization was implemented to segment the relevant regions in the breast ... -
Segmentation of Irrelevant Regions using Color Thresholding Method: application in Breast Histopathology Images
(IOP Publishing, 2019)Segmentation of irrelevant regions in the breast histopathology image is essentially performed in preliminary or post processing stages. This study presents a color thresholding method to segment the irrelevant regions, ... -
Mitotic Cell Detection in Breast Histopathology Image: a review
(IOP Publishing, 2019)Mitotic assessment is one of the critical features in the Nottingham Histological Grading (NHG) system for breast cancer grading. In recent years, rapid development in the performance of mounted camera, computer processing ... -
Intelligent Fuzzy PD+I Controller with Stabilizer for Nano Satellite Attitude Control System
(IOP Publishing, 2019)This paper discusses the variation of proportional and derivative gains in a system under the control of PD+I controller that uses fuzzy inference method an effort is made to design the fuzzy proportional-derivative (PD) ... -
An Automated Intelligent Identification and Counting System Procedure for Tuberculosis
(IOP Publishing, 2019)Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis or TB Bacilli. Currently, the classification of TB bacilli is carried out by microbiologist by using Ziehl-Nielsen (ZN) stained smear sputum ... -
Image Enhancement using Modified Partial Contrast Technique in Ziehl-Neelsen Sputum Slide Images
(IOP Publishing, 2019)Image contrast and brightness for sputum slide images are among important factors that can affect the accuracy of image analysis process. Microscopic images usually have the problem of low contrast and blurry, which are ... -
Fusion noise-removal technique with modified dark-contrast algorithm for robust segmentation of acute leukemia cell images
(Universitas Ahmad Dahlan, 2018-11)Segmentation is the major area of interest in the field of image processing stage. In an automatic diagnosis of acute leukemia disease, the crucial process is to achieve the accurate segmentation of acute leukemia blood ... -
3D object recognition using 2D moments and HMLP network
(IEEE Conference Publications, 2004-07)This paper proposes a method for recognition and classification of 3D objects using 2D moments and HMLP network. The 2D moments are calculated based on 2D intensity images taken from multiple cameras that have been arranged ... -
3D object recognition system using multiple views and cascaded multilayered perceptron network
(IEEE Conference Publications, 2004-12)This paper proposes an effective method for recognition and classification of 3D objects using multiple views technique and neural networks system. In the processing stage, we propose to use 2D moment invariants as the ... -
Measuring blood pressure using a photoplethysmography approach
(Springer-Verlag, 2008-06)Blood pressure is often measured using a device called a sphygmomanometer, a stethoscope, and a blood pressure cuff. All the existing manual or automatic measuring techniques of blood pressure are based on this principle, ... -
Blood cell image segmentation: a review
(Springer-Verlag, 2008-06)Image processing technique involved five basic components which are image acquisition, image preprocessing, image segmentation, image post-processing and image analysis. The most critical step in image processing is the ... -
Measuring of systolic blood pressure based on heart rate
(Springer-Verlag, 2008-06)In this paper, we describe the method of noninvasive blood pressure (BP) measurement using electrocardiography (ECG) signal to measure arterial blood pressure. Here, we propose a continuous blood pressure monitoring method ... -
Image enhancement techniques using local, global, bright, dark and partial contrast stretching for acute leukemia images
(International Association of Engineers, 2009-07)Leukaemia is a malignant disease (cancer) that affects people in any age either they are children or adults over 50 years old. Nowadays, there are screening system guidelines for leukaemia patients. The screening result ... -
Colour image segmentation approach for detection of malaria parasites using various colour models and k-means clustering
(World Scientific and Engineering Academy and Society (WSEAS), 2013-01)Malaria is a serious global health problem that is responsible for nearly one million deaths each year. With the large number of cases diagnosed over the year, rapid detection and accurate diagnosis of malaria infection ... -
Detection of tuberculosis bacilli in tissue slide images using HMLP network trained by Extreme Learning Machine
(Kauno Technologijos Universitetas, 2012-04)This paper proposes an automated detection of tuberculosis bacilli in Ziehl-Neelsen-stained tissue slides using image processing and neural network. Image segmentation using CY-based colour filter and k-mean clustering ... -
Classification of acute leukemia sub-types using artificial neural network
(Universiti Malaysia Perlis (UniMAP), 2012-06-18)This paper presents a study on sub-types classification of acute leukemia using artificial neural networks. Thirteen morphologival features have been extracted from acute leukemia cells and used as the neural network inputs ... -
An overview of analysis on ECG signal for heart disease
(Universiti Malaysia Perlis (UniMAP), 2012-06-18)The heart is the most important organ in the human body. The malfunctioning of the heart itself can be fatal to one’s life. The heart is built up from a myogenic muscular organ consist of a circulatory system which is ... -
An overview of acute leukemia: Blood cell segmentation and classification
(Universiti Malaysia Perlis (UniMAP), 2012-06-18)Morphological evaluation and classification of peripheral blood and bone marrow samples is one of the standard diagnostic procedures for acute leukemia. The morphological diagnosis involves manually distinguishing cells ...
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