Search Results - (( basic indicator detection algorithm ) OR ( java implementation phase algorithm ))

Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…All the algorithm for the engine has been developed by using Java script language. …”
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Forgery detection in medical images using Complex Valued Neural Network (CVNN) by Olanrewaju, Rashidah Funke, Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Zeki, Akram M., Aburas, Abdurazzag Ali

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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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Proposed fatigue index for the objective detection of muscle fatigue using surface electromyography and a double-step binary classifier by Qassim, Hassan M., Hasan, Wan Zuha Wan, Ramli, Hafiz R., Harith, Hazreen Haizi, Inche Mat, Liyana Najwa, Ismail, Luthffi Idzhar

“…This paper presents an algorithm that employs a new fatigue index for the objective detection of muscle fatigue using a double-step binary classifier. …”
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Moving detection using cellular neural network (CNN) by Prema Latha, Subramaniam

“…Ten images are selected to be used in this project. The algorithm created is used to detect the ball in the images. …”
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Face Detection System / Chan Beh Teng by Chan, Beh Teng

“…The system will generate an output where every detected face will be indicated with a rectangle on a copy of the original image. …”
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Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

“…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review by Mat Ripah N.A., Abdul Latif A., Che Cob Z., Mohd Drus S., Md Anwar R., Mohd Radzi H.

“…The use of social media, as well as computational tools and machine learning algorithm, contributes to current public health efforts to detect any indicators of depression from sources close to patients. � 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.…”

Image Based Oil Palm Tree Crowns Detection by Muhammad Afif Zakwan, Zaili

“…Image Based Oil Palm Tree Crowns Detection system is a basic system that enables the detection of oil palm tree crowns from red, green and blue (RGB) aerial images. …”
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Water Pollution Source Identification Based on Real-Time Monitoring System in Siak River by Kadir, E.A., Listia Rosa, S., Othman, M.

“…Location of sources pollution identified and the exact location found at the sensor node number 2 and 4 which indicated by abnormal reading data, various kind of material contained into river detected by the sensors system. …”
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Image Copy-Move Forgery Detection Algorithms Based on Spatial Feature Domain by Ahmed I.T., Hammad B.T., Jamil N.

Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation by Chen, Soong Der

“…This thesis focuses on ways to improve the existing solutions in the algorithmic and implementation aspects. For the algorithmic aspect, the basic principles of motion compensated DCT block-based compression scheme was studied. …”
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Analysis of watermarking techniques in video by Shojanazeri, Hamid, Wan Adnan, Wan Azizun, Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Saripan, M. Iqbal

“…Thus, research in copyright protection mechanisms, where one of which includes digital watermarking has been receiving an increasing interest from scientists especially in designing a seamless algorithm for effective implementation. Basically digital watermarking involves embedding secret symbols known as watermarks within video data which can be used later for copyright detection purposes. …”
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Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks by Najmun, Najmun

“…The results of the tests indicated increased performance in terms of fewer false positives, less CPU utilisation, less control channel bandwidth used, higher packet delivery ratio, and fewer flow requests made to the controller with 99.56% detection accuracy as compared to selected benchmarks. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…Therefore, the use of water quality indicators to detect the presence of pollutants is very important. …”
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Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

“…The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. The methods have been applied for detecting, clustering and classification polycrystalline solar wafer images, corresponding to defects such as micro cracks, stain, and fingerprints. …”
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Recovery of tree community composition across different types of anthropogenic disturbances and characterization of their effect using Landsat time series in Bornean tropical monta... by Keiko Ioki, Daniel James, Phua, Mui How, Satoshi Tsuyuki, Nobuo Imai

“…We also investigated the use of metrics from spectral trajectories of a Landsat time series (LTS) change detection algorithm (LandTrendr) to identify characteristics of disturbance events and their linkage to the recovery of tree community composition, with field validation. …”
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Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

“…In the experiment, we study the effect of introducing the outlier detection in RAN-LSH. As a result, by introducing the outlier detection, we confirm that the detection accuracy is enhanced on 377$ 3(53867$.$$1781.8781$0,1$+ average over the testing period. …”
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Robust Kernel Density Function Estimation by Dadkhah, Kourosh

“…The research also develops two new approaches for outlier and potential outlier detection in unimodal and multimodal distributions. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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