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

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

“…The performance of the SVM classification using SIFT feature is compared with the similar algorithm with SIFT-PCA combined feature. …”
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Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

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

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

Subjects: “…Algorithms…”
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Improved SIFT algorithm for place categorization by Said, Yunusa Ali, Marhaban, Mohammad Hamiruce, Ahmad, Siti Anom, Ramli, Abd Rahman

“…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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Automatic keypoints extraction from UAV image with refine and improved scale invariant features transform (RI-SIFT) by Dibs, Hayder, Idrees, Mohammed Oludare, Saeidi, Vahideh, Mansor, Shattri

“…First the RI- SIFT algorithm was used to detect and extract CPs from two overlapping UAV images. …”
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Analysis Of Sift And Surf Algorithms For Image Mosaicing On Embedded Platform by Ooi , Chong Wei

“…Experimental results shows that SURF and SIFT are robust algorithm performing stable key point detection. …”
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AMOR: an adaptive, multimodal architecture for visual object recognition by James Mountstephens

“…Reka bentuk seni bina telah dirasmikan secara matematik dan algorithmically dalam bentuk "Pengkelasan'…”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

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

“…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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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…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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Panoramic image matching method for UAV remote sensing based of sift algorithm by Emran Izzuddin Mohd Suib

Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…The average classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms are 97.28 and 97.91 respectively. …”
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A biometric fingerprint recognition system utilizing the Scale Invariant Feature Transform (SIFT) algorithm for border crossing by Hamzah N.A., Jaaz Z.A., Al-Bakri N.F., Tawfeq J.F., Radhi A.D.

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

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

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

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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACOMV-SVM algorithm is able to simultaneously tune SVM parameters and feature subset selection. …”
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Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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