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Enhance foreign body image using partitioned iterated function system (PIFS) in image enhancement technique / Hidayah Sharif by Sharif, Hidayah

“…This prototype was developed to enhance foreign body images using Partitioned Iterated Function System (PIFS). …”
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Development of Iterative Minimum-Maximum Filter for Reducing Impulse Noise from Highly Corrupted Images by Jabir, Amjad Najim

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Artificial Intelligence Application in Power Generation Industry: Initial considerations by Ismail R.I.B., Ismail Alnaimi F.B., Al-Qrimli H.F.

Detection and Measurement System for Button Mushrooms Using Convolutional Neural Network by Yong, Lio Wei, Ambar, Radzi, Abd Wahab, Mohd Helmy, Abd Jamil, Muhammad Mahadi, Choon, Chew Chang

“…Hence, an automated detection and measurement system for button mushrooms has been developed using image processing techniques based on convolutional neural network (CNN) algorithm model known as YOLOv4. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

“…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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Quantitative analysis evaluation of image reconstruction algorithms between digital and analog PET-CT by Chen, Ew-Jun *, Haniff Shazwan, Safwan Selvam, Lee, Hee Siang, Chew, Ming Tsuey *

“…Ordered Subset Expectation Maximisation (OSEM) is a widely used statistical iterative reconstruction algorithm in PET-CT due to its dependability, reconstruction quality and adequate signal-to-noise ratio. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

“…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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Online bit error rate estimation-based stopping criterion for turbo decoding by Mohamad, Roslina

“…To achieve this particular target, the convergence and non-convergence behaviours of BER in iterative decoding are investigated. In addition, the enhancement of CNCO detection is formulated using the OBE algorithm. …”
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Shape Reconstruction using Overset Grid Generation Method with an Iterative Inversion Technique by Azarina, Binti Azman

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Development of a detection and classification method for induction motor faults using Motor Current Signature Analysis and Feedforward Neural Network / Felicity Bulan Leo Uchat by Leo Uchat, Felicity Bulan

“…As it is important to choose proper training algorithm for training the FNN, therefore three different FNN training algorithms are compared in terms of their accuracy, number of iterations and training time.…”
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Breast cancer disease classification using fuzzy-ID3 algorithm based on association function by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Zalmiyah, Zakaria, Sutikno, Tole

“…The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. …”
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3D face registration across pose variation and facial expression using cross profile alignment by Anuar, Laili Hayati

“…The experiment conducted on challenging 3D face databases yields good results with 94.77% detection rate for the nose tip region detection algorithm. …”
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Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar by Azahar, Nur Adriana Qaisara

“…This study presents a fish detection system that uses Convolutional Neural Networks (CNNs) and advanced image processing techniques, with a flexible research approach directing the iterative development process. …”
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Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection by Yong, Guang

“…Therefore, two automated procedures are developed to determine these parameters iteratively. …”
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DurianCare: optimising trunk disease detection and precision farming in a mobile application / Muhammad Haziq Azmi by Azmi, Muhammad Haziq

“…During the application's development, a wide literature review was conducted, users were interviewed and surveyed, and the developed application was iteratively built and redesigned. …”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

“…This paper reports on the development of an innovative technique to detect bacteria- or virus-infected chickens based on the optical chromaticity of the chicken comb. …”

Hyperspectral imaging for detection of macronutrients retained in glutinous rice under different drying conditions by Jimoh, Kabiru Ayobami, Hashim, Norhashila, Shamsudin, Rosnah, Che Man, Hasfalina, Jahari, Mahirah, Megat Ahmad Azman, Puteri Nurain, Onwude, Daniel I.

“…Therefore, the developed SGID-VISSA-PLSR can be used to build a smart and reliable spectral system for detecting the macronutrients in GR grains.…”
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Deep learning based human presence detection by Venketaramana, Balachandran, Muhammad Nur Aiman, Shapiee, Ahmad Fakhri, Ab. Nasir, Mohd Azraai, Mohd Razman, Anwar P. P., Abdul Majeed

“…It will cover the fundamentals of modern deep learning based object detectors and the methods to accomplish the human presence detection task. The YOLO family of object detectors have truly revolutionized the Computer Vision and object detection industry and have continuously evolved since its development. …”
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application by Aminordin, Azmi

“…Two approaches introduced to detect malware in Android mobile environment namely static analysis and dynamic analysis. …”
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Glove defect detection via YOLO V5 by Yong, Chen How, Ahmad Fakhri, Ab. Nasir, Khairul Fikri, Muhammad, Anwar P. P., Abdul Majeed, Mohd Azraai, Mohd Razman, Muhammad Aizzat, Zakaria

“…There are three crucial parts to develop an effective defect glove detection model, which are data collection, model development and model evaluation. …”
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