Search Results - ((sift algorithm) OR (svm algorithm))

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  1. 1

    Waste classification using support vector machine with SIFT-PCA feature extraction by Puspaningrum, Adita Putri, Endah, Sukmawati Nur, Sasongko, Priyo Sidik, Kusumaningrum, Retno, ., Khadijah, ., Rismiyati, Ernawan, Ferda

    Published 2020
    “…The performance of the SVM classification using SIFT feature is compared with the similar algorithm with SIFT-PCA combined feature. …”
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    Conference or Workshop Item
  2. 2

    Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

    Published 2015
    “…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. This study adopted supervised machine learning algorithm which is the Support Vector Machine (SVM) for classification. …”
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    Final Year Project Report / IMRAD
  3. 3

    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

    Published 2018
    “…The performance of the proposed algorithm is compared to that of several state-of-the-art TVS algorithms. …”
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    Thesis
  4. 4

    Facial features point localization using modified SIFT scale space / Zulfikri Paidi by Paidi, Zulfikri

    Published 2020
    “…Three tests were used on the original SIFT algorithm and modified SIFT. The first test is to evaluate the accuracy of the built-in vector feature. …”
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    Thesis
  5. 5

    Improved SIFT algorithm for place categorization by Said, Yunusa Ali, Marhaban, Mohammad Hamiruce, Ahmad, Siti Anom, Ramli, Abd Rahman

    Published 2015
    “…The main aim of this paper is an improvement of the famous Scale Invariant Feature Transform (SIFT) algorithm used in place categorization. Masking approach to reduce the computational complexity of SIFT have been proposed. …”
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    Conference or Workshop Item
  6. 6

    AMOR: an adaptive, multimodal architecture for visual object recognition by James Mountstephens

    Published 2014
    “…Reka bentuk seni bina telah dirasmikan secara matematik dan algorithmically dalam bentuk "Pengkelasan'…”
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    Research Report
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    Analysis Of Sift And Surf Algorithms For Image Mosaicing On Embedded Platform by Ooi , Chong Wei

    Published 2015
    “…Experimental results shows that SURF and SIFT are robust algorithm performing stable key point detection. …”
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    Thesis
  9. 9

    Enhanced faster region-based convolutional neural network for oil palm tree detection by Liu, Xinni

    Published 2021
    “…Hence, this research aims to close the research gaps by exploring the deep learning-based object detection algorithm and the classical convolutional neural network (CNN) to build an automatic deep learning-based oil palm tree detection and counting framework. …”
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    Thesis
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    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…The first two algorithms, ACOR-SVM and IACOR-SVM, tune the SVM parameters while the second two algorithms, ACOMV-R-SVM and IACOMV-R-SVM, tune the SVM parameters and select the feature subset simultaneously. …”
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    Thesis
  12. 12

    Effect of masking techniques on computational complexity reduction of scale invariant feature transform by Sai'd, Yunusa Ali

    Published 2015
    “…The Scale Invariant Feature Transform (SIFT) is algorithm use in feature detection and description, it is famous and has dominated the research community. …”
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    Thesis
  13. 13

    Arabic words recognition technique for pattern matching using SIFT, SURF and ORB by Mohd Zailani, Syarah Munirah, Morshidi, Malik Arman, Mohd Esa, Luqman Naim

    Published 2017
    “…This paper investigates which recognition technique suits better in matching an image of printed Arabic text. The recognition algorithm involves the conventional Scale-Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF) and Oriented FAST and Rotated BRIEF (ORB). …”
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    Article
  14. 14

    Image authentication using Scale Invariant Feature Transform (SIFT) / Nurul Anis Suriana Adnan by Adnan, Nurul Anis Suriana

    Published 2017
    “…The proposed system is based on Scale Invariant Feature Transform (SIFT) algorithm that is invariant to translations, rotations, and scaling information in the image domain.…”
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    Thesis
  15. 15

    Integrated ACOR/IACOMV-R-SVM Algorithm by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2017
    “…The first algorithm, ACOR-SVM, will tune SVM parameters, while the second IACOMV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. …”
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    Article
  16. 16

    IMAGE STITCHING USING HARRIS CORNER & SIFT FEATURES by SHAMSUL KAMAR, FARAH AZLIN

    Published 2016
    “…In this project work, the objective is to implement and design an algorithm of image stitching construction with approaches of two types of feature based, which are Harris corner and Scale-Invariant Feature Transform (SIFT) features method. …”
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    Final Year Project
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    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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    Article
  19. 19

    Keypoint Descriptors in SIFT and SURF for Face Feature Extractions by Suk, Ting Pui, Minoi, Jacey Lynn

    Published 2018
    “…The last decade, numerous researches are still working on developing a robust and faster keypoints image descriptors algorithm. In this paper, we will review a few complex keypoint descriptor approaches that are well-known and commonly used in vision applications, and they are Scale Invariant Feature Transform (SIFT) and Speed-up Robust Features (SURF). …”
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    Proceeding
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    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…The average classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms are 97.28 and 97.91 respectively. …”
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    Article