Ghazanfar Latif

Ghazanfar Latif
University of Québec in Chicoutimi | UQAC · Department of Computer Sciences and Mathematics (DIM)

PhD in Computer Science
Research and Development in Deep Learning, Computer Vision, Machine Learning, Data Science, NLP, AI, Image Processing

About

75
Publications
60,206
Reads
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523
Citations
Introduction
I am doing research in the field of Artificial Intelligence, Machine Learning, Image Processing, Internet of Things and Robotics.
Additional affiliations
January 2019 - present
Prince Mohammad University
Position
  • Project Manager
January 2014 - January 2019
Prince Mohammad University
Position
  • Instructor
August 2010 - September 2011
MTBC - A Unique Healthcare IT Company
Position
  • Analyst
Description
  • I worked as cloud Manager and Research Analyst for deployment of MTBC Electronic Health Record (EHR) Management System.
Education
January 2016 - September 2019
University Malaysia Sarawak
Field of study
  • Computer Science (Deep Learning)
September 2011 - December 2013
September 2006 - May 2010

Publications

Publications (75)
Article
Full-text available
Brain tumor diagnosis is a very crucial task. This system provides an efficient and fast way for diagnosis of the brain tumor. Proposed system consists of multiple phases. First phase consists of texture feature extraction from brain MR images. Second phase classify brain images on the bases of these texture feature using ensemble base classifier....
Article
Full-text available
In medical field visualization of the organs is very imperative for accurate diagnosis and treatment of any disease. Brain tumor diagnosis and surgery also required impressive D visualization of the brain to the radiologist. Detection and D reconstruction of brain tumors from MRI is a computationally time consuming and error-prone task. Proposed sy...
Article
Full-text available
Rice is considered one the most important plants globally because it is a source of food for over half the world’s population. Like other plants, rice is susceptible to diseases that may affect the quantity and quality of produce. It sometimes results in anywhere between 20–40% crop loss production. Early detection of these diseases can positively...
Article
Full-text available
COVID-19 which was announced as a pandemic on 11 March 2020, is still infecting millions to date as the vaccines that have been developed do not prevent the disease but rather reduce the severity of the symptoms. Until a vaccine is developed that can prevent COVID-19 infection, the testing of individuals will be a continuous process. Medical person...
Patent
Full-text available
A device, method, and system for converting printed Braille dots to speech. A Braille image of the printed Braille dots is captured by a digital camera mounted on a 3D ring case. Data processing and one or more image recognition operations are performed by a microprocessor to match the Braille image to a textural character corresponding to the Brai...
Article
Full-text available
Diabetic Retinopathy (DR) is a medical condition present in patients suffering from long-term diabetes. If a diagnosis is not carried out at an early stage, it can lead to vision impairment. High blood sugar in diabetic patients is the main source of DR. This affects the blood vessels within the retina. Manual detection of DR is a difficult task si...
Patent
Full-text available
Methods, systems, and computer readable media to detect and model a brain tumor in an electronic image and to predict features of the brain tumor based on the model. The method can include classifying one or more magnetic resonance imaging (MRI) images of a brain into one or more of one or more tumorous images containing an image of a tumor or one...
Article
Full-text available
Author verification of handwritten text is required in several application domains and has drawn a lot of attention within the research community due to its importance. Though, several approaches have been proposed for the text-independent writer verification of handwritten text, none of these have addressed the problem domain where author verifica...
Article
Full-text available
The complexity of brain tissue requires skillful technicians and expert medical doctors to manually analyze and diagnose Glioma brain tumors using multiple Magnetic Resonance (MR) images with multiple modalities. Unfortunately, manual diagnosis suffers from its lengthy process, as well as elevated cost. With this type of cancerous disease, early de...
Article
Full-text available
A multitude of applications in engineering, ore processing, mineral exploration, and environmental science require grain recognition and the counting of minerals. Typically, this task is performed manually with the drawback of monopolizing both time and resources. Moreover, it requires highly trained personnel with a wealth of knowledge and equipme...
Article
Full-text available
Background: The task of identifying a tumor in the brain is a complex problem that requires sophisticated skills and inference mechanisms to accurately locate the tumor region. The complex nature of the brain tissue makes the problem of locating, segmenting, and ultimately classifying Magnetic Resonance (MR) images a complex problem. The aim of th...
Article
Full-text available
It became apparent that mankind has to learn to live with and adapt to COVID-19, especially because the developed vaccines thus far do not prevent the infection but rather just reduce the severity of the symptoms. The manual classification and diagnosis of COVID-19 pneumonia requires specialized personnel and is time consuming and very costly. On t...
Article
PurposePneumonia detection is usually done by specialized highly trained specialists through the review of chest radiographs combined with vital signs, laboratory exams, and medical history. Though the presence of pneumonia in images appears in the form of areas of high opacity in the lungs which is difficult to differentiate from opaque areas caus...
Article
Full-text available
The needs of persons with disabilities are still being undermined even though persons with disabilities have proven to be productive members of the community when given the right education, support, and tools. Assistive devices are being designed, developed, and sold to provide persons with disabilities the tools to be able to become productive mem...
Chapter
Lung cancer is second cancer common to men and women as well as it is one of the world's highest cause of death. Reports in recent years have shown that standard X-rays are not effective in diagnosing lung cancer. It has clinically established that low-dose computed tomography (LDCT)-based diagnosis helps to decreases mortality from lung cancer by...
Chapter
Braille is a system that is designed to assist visually impaired individuals to acquire information. It consists of raised dots arranged in a cell of three rows and two columns. Visually impaired individuals rely on the sense of touch to read and write. However, it is difficult to memorize the arrangement of dots that compose a character. This rese...
Article
Full-text available
Background Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques. Objective In this paper, a comprehensive review is presented on all thirteen variations of FCM segmentation techniques. In the review pro...
Chapter
Internet of Things (IoT), cloud computing, fog computing, and other new technologies are expected to transform the healthcare industry among other. This chapter discusses the use of an automated system based on IoT, cloud and fog computing for constant monitoring of the patient’s health, dispensing medicinal dosage in a timely manner and other comp...
Article
Full-text available
With the increase in demand for bandwidth-thirsty cloud-based services, bandwidth demands for rack-to-rack interconnect in data centers are increasing exponentially. In this paper, an optical interconnect architecture dubbed “POID” is proposed. The novel architecture is proposed using passive optical technology, wavelength division multiplexing, an...
Article
Full-text available
Reciprocal optimality is a desirable characteristic from the end user perspective, for both Best Effort and Quality of Service (QoS) datagrams delivery within a network. A cohesive solution to such issues is the expected outcome of this work. It is also aimed to formulate and evaluate enhanced scheduling algorithm for packets delivery, focusing on...
Article
The agriculture industry is of great importance in many countries and plays a considerable role in the national budget. Also, there is an increased interest in plantation and its effect on the environment. With vast areas suitable for farming, countries are always encouraging farmers through various programs to increase national farming production....
Article
Full-text available
Internet of Things (IoT) is changing the way many sectors operate and special attention is paid to promoting healthy living by employing IoT based technologies. In this paper, a novel approach is developed with IoT prototype of Wireless Sensor Network and Cloud based system to provide continuous monitoring of a patient’s health status, ensuring tim...
Chapter
As a result of the recent developments that swept through the petroleum industry, the Internet of things (IoT) became a part of the main applied technologies in the past few years. This chapter illustrates how the future depends on IoT in building intelligent oil fields and oil wells. Major benefits and challenges of using IoT as discussed. It also...
Chapter
The Internet of things (IoT) has become one of the principle applied technologies in the past few years. In this chapter, you will read about how the IoT has an impact on certain fields and on human daily life. You will also read about the basic features of Smart Cities and why a modern city is given that name, along with some of its problems and s...
Chapter
Modern technology has developed at a fast pace, with many types of technology competing against each other. However, the Internet of Things (IoT) has superseded many new technologies. IoT basically consists of algorithms that obtain your retail habits more than what can be probably assumed. IoT capabilities allow devices and sensors to communicate...
Article
Background Detection of brain tumor is a complicated task which requires specialized skills and interpretation techniques. Accurate brain tumor classification and segmentation from MR images provide an essential choice for medical treatments. The different objects within an MR image have similar size, shape, and density which makes the tumor classi...
Article
Full-text available
Handwritten character and numeral recognition have gained interest in the research community as part of the big picture of Machine Learning. Writer independent recognition systems are still in the working and the research is geared towards an optimized technique that can achieve this. In this paper, we propose a numeral recognition system that form...
Article
Full-text available
In this study, cloud based innovative methods are introduced that allow users with motor skills impairments to access the customized learning platforms. The complete methodology relies on the development of existing technology originally developed for the Gaming Industry; Microsoft Xbox Kinect Sensor. A novel learning platform is developed for teac...
Poster
Full-text available
Design of a system that recognize handwritten Arabic words written by children aging between 7-10 years old. This project is intended to transform Arabic handwritten words to its digital form to provide the correct writing and then grade it accordingly. The project will depend heavily on the fundamentals of machine learning using deep learning tech...
Conference Paper
This paper proposes a new parallel support vector machine (PSVM) that is efficient in terms of time complexity. Support vector machine is one of the popular classifiers for analysis of data and classification of patterns. However, SVM requires a large memory (in the range of 100 GB or more) in order to process big-data (i.e., in the range of 1 TB d...
Article
Full-text available
With the advent of powerful and low cost Single Board Computers (SoC), developing fully automated systems is becoming a trivial task. We can sense objects and capture images by using embedded systems to process and perform action accordingly. License Plate (LP) recognition systems use optical character recognition techniques to detect number plate...
Article
Full-text available
A fully-labelled dataset of Arabic Sign Language (ArSL) images is developed for research related to sign language recognition. The dataset will provide researcher the opportunity to investigate and develop automated systems for the deaf and hard of hearing people using machine learning, computer vision and deep learning algorithms. The contribution...
Article
Full-text available
Automatic detection and recognition of traffic signs is very important and could potentially be used for driver assistance to reduce accidents and eventually in driverless automobiles. In this paper, Deep Convolutional Neural Network (CNN) is used to develop an Autonomous Traffic and Road Sign (ATRS) detection and recognition system. The proposed s...
Article
Full-text available
Diabetic Retinopathy (DR) is an eye medical condition usually found in patients suffering from diabetes. The initial stages of DR can either show no symptoms or cause mild vision problems but advanced stages of the disease can cause blindness. The main cause of DR is high blood sugar in diabetic patients that affect the blood vessels supplying bloo...
Article
Classification of brain tumor is one of the most vital tasks within medical image processing. Classification of images greatly depends on the features extracted from the image and thus feature extraction plays a great role in the correct classification of images. In this paper, an enhanced method is presented for Glioma MR Images classification usi...
Conference Paper
In this research, an automated method is proposed for Brain tumor classification into four different types which is an important step in brain tumor diagnosis. Most of the recent research studies focus on binomial classification of brain MR image into tumorous and non-tumorous images that can be extracted using image segmentation. Further classific...
Article
Full-text available
Background: An approach based on QR decomposition, to remove speckle noise from medical ultrasound images, is presented in this paper. Methods: The speckle noisy image is segmented into small overlapping blocks. A global covariance matrix is calculated by averaging the corresponding covariances of the blocks. QR decomposition is applied to the g...
Conference Paper
Full-text available
Segmentation is the first and most important task in the diagnosis of skin cancer using computer-aided systems and due to complex structure of skin lesions, the automated process may lead to a completely different diagnosis. In this paper, a novel segmentation method of skin lesions is proposed which is both effective and simple to implement. Smoot...
Poster
Full-text available
Through in-depth research, we reached a solution for automatic brain tumor detection and prediction of tumor location, volume and type using multimodal MR Images. This work contributes to the social impact and has a very high potential for commercialization. Diagnostic and medical imaging market is worth USD 33.42 Billion by 2020, Asia-pacific mark...
Article
Background: MRI which stands for Magnetic Resonance Imaging is commonly used to capture images of internal body organs, functionality and structure. Manual analysis is usually performed by Radiologists on a large set of MR images in order to detect brain tumor. Aims: This research aims to improve automated brain MR image classification and tumor se...
Article
Full-text available
Magnetic Resonance Imaging (MRI) is considered one of the most effective imaging techniques used in the medical field for both clinical investigation and diagnosis. This is due to the fact that MRI provides many critical features of the tissue including both physiological and chemical information. Rician noise affects MR images during acquisition t...
Article
Full-text available
A technique based on Schur decomposition to supress the multiplicative (speckle) noise from medical ultrasound images is presented in this study. An image which carries the speckle noise is divided into small overlapping segments, size of these segments depends on the nature of speckle carried by the image and a global covariance matrix is calculat...
Chapter
Underwater Wireless Sensor Networks (UWSNs) have captured interest of many researchers with the desire to control the large portion of the world overspread by water. Energy efficiency is one of the major concerns in UWSNs due to the limited energy of the underwater sensor nodes. In order to enhance the network lifetime, efficient and reliable proto...
Chapter
Underwater wireless sensor networks (UWSNs) find applications in various aspect of life like the tsunami and earthquake monitoring, pollution monitoring, ocean surveillance for defense strategies, seismic monitoring, equipment monitoring etc. The sensor node consumes more energy and load distribution suffer from imbalance at long distance. In this...
Chapter
Underwater Wireless Sensor Networks (UWSNs) facilitate an extensive variety of aquatic applications such as military defense, monitoring aquatic environment, disaster prevention, etc. However UWSNs routing protocols face many challenges due to adverse underwater environment such as high propagation and transmission delays, high deployment cost, nod...
Conference Paper
Routing hole problem is one of the most important issues in the underwater wireless sensor networks (UWSNs). It aims to analyze the routing hole boundary to prevent the formation of routing hole such that network lifetime and all other parameters are also increased. In this paper, we have proposed the two techniques to transmit the data in the pres...
Conference Paper
Underwater Wireless Sensor Networks (UWSNs) have captured interest of many researchers with the desire to control the large portion of the world overspread by water. Energy efficiency is one of the major concerns in UWSNs due to the limited energy of the underwater sensor nodes. In order to enhance the network lifetime, efficient and reliable proto...
Conference Paper
Underwater Wireless Sensor Networks (UWSNs) facilitate an extensive variety of aquatic applications such as military defense, monitoring aquatic environment, disaster prevention, etc. However UWSNs routing protocols face many challenges due to adverse underwater environment such as high propagation and transmission delays, high deployment cost, nod...
Conference Paper
Underwater wireless sensor networks (UWSNs) find applications in various aspect of life like the tsunami and earthquake monitoring, pollution monitoring, ocean surveillance for defense strategies, seismic monitoring, equipment monitoring etc. The sensor node consumes more energy and load distribution suffer from imbalance at long distance. In this...