Search Results - (( pattern detection system algorithm ) OR ( using solution using algorithm ))

Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki by Mohd Zaki, Sofea Najihah

“…This project attempts to accurately detect the type of dyslexic handwriting. Convolutional Neural Network (CNN) algorithm was chosen as one of the possible solutions after a thorough analysis of many algorithms for dyslexic handwriting identification. …”
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Development of shape pattern recognition for fpga-based embbeded object tracking system by Fauziliana, Binti Osman

“…There are lots of algorithms available including the detection of handwriting, moving people, animals and the barcode number. …”
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Hybrid of rough set theory and Artificial Immune Recognition System as a solution to decrease false alarm rate in intrusion detection system by Sabri F.N.M., Norwawi N.M., Seman K.

Real-time face recognition system in smart classroom using Haar cascade and local binary pattern model by Mohamed, Raihani, Jafni, Jaffrina Umaira, Mohd Rum, Siti Nurulain

“…The face recognition system is proposed to use the Haar Cascades algorithm to detect individual faces of students while using Local Binary Pattern (L B P) is used to identify and verify students’ identity by using their facial features. …”
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

“…Anomaly-based Intrusion Detection System (IDS) uses known baseline to detect patterns which have deviated from normal behaviour. …”
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Underwater Image Recognition using Machine Learning by Divya, N.K., Manjula, Sanjay Koti, Priyadarshini, S

“…Machine Learning is the branch of Artificial Intelligence in which a computer is fed with data and based on that data it tries to find out solution on its own. It encompasses the procedure for feeding algorithms information to create the algorithms realize patterns in the data and then increase the performance of the algorithms. …”
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Smartphone aided real-time blood vein detection system by Ahmed, Kazi Istiaque, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

“…Illuminated infrared light in the blood cells of the vein is absorbed due to the manifestation of the Haemoglobin in blood and the IR non-blocking camera can capture the vein patterns in the IR light spectrum. Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm was used to enhance the pattern of the vein in the Android application developed using OpenCV3. …”
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Leveraging Web Scraping in Predictive Modelling of Supply Risk Detection by Ng, Shi Ya

“…By collecting data from news sites, this system is aimed to provide data for predictive modelling so it can be used to detect patterns in supply risks to create and predict the probability of a temporary event occurring in the future…”
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Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

“…The set of rules can be used as part of the knowledge base in expert system or decision support system for financial institutions.…”
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Scrutinized System Calls Information Using J48 And Jrip For Malware Behaviour Detection by Abdollah, Mohd Faizal, S. M. M Yassin, S. M. Warusia Mohamed, Mohd Saudi, Nur Hidayah

“…This integrated classifier algorithm applied to analyse, classify and generate rules of the pattern and program behaviour of system call information in which, the legal and illegal behaviours could identify. …”
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Transformer-Based Model for Malicious URL Classification by Do N.Q., Selamat A., Lim K.C., Krejcar O., Ghani N.A.M.

Anomaly detection of intrusion based on integration of rough sets and fuzzy c-means by Chimphlee, Witcha, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan, Chimphlee, Siriporn

“…New intrusion types, of which detection systems are unaware, are the most difficult to detect. …”
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor by Mohamad Nor, Ahmad Azhari

“…Results include descriptive and correlation analysis revealing crucial primary cooling system data patterns. Predictive modelling using k-nearest neighbour demonstrates high accuracy, precision, and recall metrics, while decision tree modelling raises considerations for further refinement. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

“…Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. …”
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Game theoretic approach for exhaustive tactical modelling of node misbehavior in adhoc networking based IOT paradigm/P-RIGS18-020-0020 by Olanrewaju, Rashidah Funke Olanrewaju, Anwar, Farhat, Khan, Burhan Ul Islam

“…On comparing our results with the existing systems, it was found that the proposed algorithm performed better in the detection of malicious nodes, throughput, false positive rate and detection of attacks.…”
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IoT based drainage monitoring system by Venoth, Abhinaashgovin, Sankaran, Sukhiirtan, Velan, Sheshan, Moganthera Thevar, Atishvar, Saravanan, Sharvin

“…This real-time data is wirelessly transmitted to a central monitoring system, where it is analysed using advanced algorithms. …”
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Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB) by Hashim, Nurul Akmal

“…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.