Search Results - (( using vector method algorithm ) OR ( automatic identification using algorithm ))

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  1. 1

    Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

    Published 2013
    “…To do this, at first, based on the proposed algorithm,the physiological dimensions of leaves are automatically measured and with regard to these parameters, specified features such as shape, morph, texture and colour are extracted from the image of the plant leaf through image processing to create a reserved feature database to be used for different species of plants. …”
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    Thesis
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    Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

    Published 2019
    “…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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    Article
  3. 3

    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

    Published 2019
    “…The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. …”
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    Article
  4. 4

    Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image by Shojanoori, Razieh

    Published 2016
    “…The method of maximum likelihood classification and support vector machines leads to the lowest classification accuracy since these algorithms extract only the spectral information of each pixel and consequently fail to utilize spatial, color and textural information.…”
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    Thesis
  5. 5

    Designing an integrated AIOT system for tracking class attendance by Kuak, Xuan Ren

    Published 2024
    “…Basics and ensures that the software is more secure than the previous traditional attendance method using roll-less slides. For face detection the system uses a YOLO (You Only Look Once) algorithm, which allows quick and efficient recognition of student faces in the classroom context. …”
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    Final Year Project / Dissertation / Thesis
  6. 6

    Advances in automatic insect classification by Hassan, Siti Noorul Asiah, Abdul Rahman, Nur Nadiah Syakira, Htike@Muhammad Yusof, Zaw Zaw, Shoon , Lei Win

    Published 2014
    “…This paper details advances in insect recognition, discussing representative works from different types of method and classifiers algorithm. Among the method used in the previous research includes color histogram, edge detection and feature extraction (SIFT vector). …”
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    Article
  7. 7

    New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz by Ab. Aziz, Nur Fadilah

    Published 2014
    “…Another new hybrid algorithm that used Evolutionary Programming (EP) termed as Evolutionary Support Vector Machine (ESVM) was also developed for comparative study. …”
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    Thesis
  8. 8

    Vision based entomology: a survey by Hassan, Siti Noorul Asiah, Abdul Rahman, Nur Nadiah Syakira, Htike@Muhammad Yusof, Zaw Zaw, Shoon , Lei Win

    Published 2014
    “…This paper details advances in insect recognition, discussing representative works from different types of method and classifiers algorithm. Among the method used in the previous research includes color histogram, edge detection and feature extraction (SIFT vector). …”
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    Article
  9. 9

    Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon by Lim , Pooi Khoon

    Published 2020
    “…Upon using the artifact detection method followed by BP estimation, the SBP and DBP were improved in BHS grades from D to A. …”
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    Thesis
  10. 10

    A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah by Mansoor Abdullah, Hayat

    Published 2012
    “…Then, Image segmentation applied by using canny edge detection algorithm with specific morphological operation to isolate the image objects components. …”
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    Thesis
  11. 11

    Decision-Level Fusion Scheme For Nasopharyngeal Carcinoma Identification Using Machine Learning Techniques by Mohammed, Mazin Abed, Mohd Khanapi, Abd Ghani, M.A., Burhanuddin, Arunkumar, N., Mostafa, Salama A., Ibrahim, Dheyaa Ahmed, Abdullah, Mohamad Khir, Jaber, Mustafa Musa, Abdulhay, Enas, Ramirez-Gonzalez, Gustavo

    Published 2020
    “…We have implemented the fusion of the three image texture-based schemes (local binary patterns, the first-order statistics histogram properties, and histogram of gray scale) at the decision level and tested the performance of this scheme using the same experimental setup in the previous section for simple scorelevel fusion, but for comparison, We used the classifiers methods which are support vector machines (SVM), k-nearest neighbors’ algorithm, and artificial neural network (ANN). …”
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    Article
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    Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB) by Hashim, Nurul Akmal

    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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    Thesis
  15. 15

    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    Published 2021
    “…Finally, the k-nearest neighbors ( kNN) classification technique was used for automatic gender identification of an emotional-based EEG dataset. …”
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    Article
  16. 16

    Feature extraction using spectral centroid and mel frequency cepstral coefficient for Quranic accent automatic identification by Kamarudin, Noraziahtulhidayu, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Nematollahi, Mohammad Ali, Hassan, Abd Rauf

    Published 2014
    “…This paper presents the process of Quranic Accent Automatic Identification. Recent feature extraction technique that is used for Quranic verse rule identification/Tajweed include Mel Frequency Cepstral Coefficients (MFCC) which prone to additive noise and may reduce the classification result. …”
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    Conference or Workshop Item
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    System Identification And Control Of Automatic Car Pedal Pressing System For Low-Speed Driving In A Road Traffic Delay by Lai, Chong Jin

    Published 2022
    “…Both controllers were then implemented and tested in automatic car pedal pressing system. The controller gains were tuned using metaheuristic algorithm which is Particle Swarm Algorithm (PSO) for optimal values of fuzzy controller parameters. …”
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    Undergraduates Project Papers