Search Results - ((sift algorithm) OR (((system algorithm) OR (based algorithm))))

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

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

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

“…It copied parts of the original images and pasted it elsewhere in the same image. 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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Multispectral palm vein image fusion for contactless palm vein verification system by Soh, Shi Chuan

“…SIFT algorithm achieved a reduction in EER rate by 12% in 700 nm, 8% in 850 nm, 7% in 940 nm compared with the SURF algorithm. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…To overcome this problem, in recent years, researchers obtained some achievements with combination of invariant local features such as Scale Invariant Feature Transform (SIFT) with global feature of leaf images. Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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A real-time mobile notification system for inventory stock out detection using SIFT and RANSAC by Merrad, Yacine, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Gunawan, Teddy Surya

“…The proposed method is a machine learning based real-time notification system using the exciting Scale Invariant Feature Transform feature detector (SIFT) and Random Sample Consensus (RANSAC) algorithms. …”
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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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“myHerbs”: A mobile based application for herbal leaf recognition using sift / Nur Nabilah Abu Mangshor …[et al.] by Abu Mangshor, Nur Nabilah, Abdul Rahman, Mohamed Al Arabee, Sabri, Nurbaity, Ibrahim, Shafaf, Ibrahim, Zaidah, Shari, Anis Amilah

“…In addition, it also contributes to the exploration and implementation of learning algorithm in mobile-based application.…”
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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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A keypoint based copy-move forgery detection and localization in digital images / Somayeh Sadeghi by Somayeh, Sadeghi

“…The true and false positive rates achieved by the proposed algorithm outperform several current detection algorithms.…”
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Slam-based mapping for object recognition by Loh, Wan Ying

“…The personal laptop acts as the command center where the Simultaneous Localization and Mapping (SLAM) algorithm are run by receiving odometry data from Arduino on the custom made robot. …”
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Comparison of Feature Extractors for Real-Time Object Detection on Android Smartphone by Saipullah, Khairul Muzzammil

“…This paper presents the analysis of real-time object detection method for embedded system particularly the Android smartphone. As we all know, object detection algorithm is a complicated algorithm that consumes high performance hardware to execute the algorithm in real time. …”
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Biometric identification with limited data set by Lionnie, Regina, Attamimi, Said, Sediono, Wahju, Alaydrus, Mudrik

“…The best recognition precision was produced by SIFT algorithm which was 38%, while other methods only gave out 30-32% precision of recognition.…”
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Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants by Chua, Eng Wee, Goh, Chian Siang

“…SIFT assumes that important DNA bases within a gene are conserved and not amenable to substitution. …”
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ANALYSIS OF REAL-TIME OBJECT DETECTION METHODS FOR ANDROID SMARTPHONE by Saipullah, Khairul Muzzammil

“…This paper presents the analysis of real-time object detection method for embedded system, especially the Android smartphone. As we all know, object detection algorithm is a complicated algorithm that consumes high performance hardware to execute the algorithm in real time. …”
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Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

“…The urgency of early identification is underscored by the fact that diseases predominantly affect banana plant leaves. Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. …”
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Object Localization In 3D Point Cloud by Chung, Hui Sze

“…The results of object localization are often affected by many factors such as the quality of the point clouds and the sensitivity of the algorithms to the occlusion in the point clouds. This project provides an efficient algorithm that is able to recognize and localize more than one object from the scene at the same time and is also able to perform localization of an object which undergoes a transformation. …”
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