Search Results - (( recognition application optimisation algorithm ) OR ( java adaptation optimization algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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EEG-based emotion recognition using machine learning algorithms
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Final Year Project / Dissertation / Thesis -
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Leveraging transfer learning and label optimization for enhanced traditional Chinese medicine ner performance
Published 2024“…To address these challenges, this research aims to optimise the application of deep learning models for NER and achieve enhanced results. …”
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Article -
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…Overall, the MLP was considered the best optimised network followed by ANFIS and LVQ networks.…”
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Research Reports -
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…However, the FGCDR produced a substantial amount of redundant and insignificant features. The ant colony optimisation (ACO) algorithm have been used to select feature subset. …”
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Thesis -
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Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB)
Published 2017“…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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Extrema Points Application In Determining Iris Region Of Interest
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Article -
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A survey on improvement of Mahalanobis Taguchi system and its application
Published 2024Subjects:Article -
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Discrepancy and thematic bibliometric analyses of the remaining limitations in artificial intelligence
Published 2024“…Additionally, this study commends the ongoing efforts to harness AI’s computational power and algorithmic innovations to enhance AI’s overall performance and applicability.…”
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An enhanced synthetic oversampling framework with self-supervised contrastive learning for multi-class image imbalance
Published 2025“…The second contribution is the introduction of the Clustering and Nearest Centroid Neighbour-based Synthetic Minority Oversampling (CLNCN-SMOTE) algorithm to resolve multi-class imbalance. The algorithm is an enhancement of traditional K-means SMOTE that incorporates a nearest centroid neighbour strategy. …”
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Thesis