Analysis of the Relationship Between Scale Invariant Feature Transform Keypoint Properties and Their Invariance to Geometrical Transformation Applied to Cone-Beam Computed Tomograp... by Diletta Pennati, Leonardo Bocchi

“…However, SIFT was not initially developed specifically for medical imaging applications, so it is necessary to adapt the algorithm to those kinds of images. …”
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Features Image Matchingof SUＲF and ＲANSAC by WANG Wei-bing, BAI Xiao-ling, XU Qian

“…The scale invariant feature transform ( SIFT) algorithm，SUＲF algorithm，and the proposed optimization algorithm are compared in the same experimental environment. …”
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A Systematic Study on the Extraction and Image Reproduction of Ceramic Sculpture Artworks by Yuhong Wang

“…The algorithm combining SIFT and MSER to extract feature points can reach 3.6%, 4.6%, 8.4%, 15%, and 19.1%. …”
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Feature-Based Classification of Amino Acid Substitutions outside Conserved Functional Protein Domains by Branislava Gemovic, Vladimir Perovic, Sanja Glisic, Nevena Veljkovic

“…We have developed feature-based algorithm for the detection of mutations outside conserved functional domains (CFDs) and compared its classification efficacy with the most commonly used phylogeny-based tools, PolyPhen-2 and SIFT. …”
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Construction of Holographic Immersion Chamber Based on Multisource Information Fusion and Interactive Virtual Reality Technology by Chunying Wang, Yin Liu

“…The approximation index of the transformation matrix calculated by the registration algorithm based on SIFT+MSA is 1.7073, which is less than 4.0017 obtained by SIFT matching algorithm. …”
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Retracted: Fast Recognition Method of Football Robot’s Graphics From the VR Perspective by Zhen Bai, Liang Wang, Sheng Zhou, Yuan Cao, Ying Liu, Jie Zhang

“…PA-SIFT algorithm is used to quickly identify the graphics. …”
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Retracted: Target Recognition Method of Rehabilitation Robot Based on Image Local Features by Xing Li, Tianbao Wu

“…The number of correct matches accounted for 58.3%. Compared with the SIFT algorithm and the Harris+SIFT algorithm, the accuracy rate increases by 12.3% and 14.4%, respectively. …”
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Financial phishing detection method based on sensitive characteristics of webpage by Xiang-dong HU, Ke LIU, Feng ZHANG, Jia-fu LIN, Jun FU, Zhi-hui GUO

“…The method matches number of sensitive text using multiple pattern matching algorithm AC_SC (AC suitable for Chinese). Then, the method locates and cuts logo image of webpage, and utilizes PCA-SIFT algorithm to extract image features and match features with library of webpage logo which was established beforehand. …”
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Detect material volume by fusing heterogeneous camera target detection and depth estimation information by Wei Tian, Xuecong Cheng, Yipeng Zhang, Huazhi Lin

“…The visual measurement algorithm is the mainstream solution for the volume measurement. …”
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A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data. by Aaditya V Rangan, Caroline C McGrouther, John Kelsoe, Nicholas Schork, Eli Stahl, Qian Zhu, Arjun Krishnan, Vicky Yao, Olga Troyanskaya, Seda Bilaloglu, Preeti Raghavan, Sarah Bergen, Anders Jureus, Mikael Landen, Bipolar Disorders Working Group of the Psychiatric Genomics Consortium

“…A common goal in data-analysis is to sift through a large data-matrix and detect any significant submatrices (i.e., biclusters) that have a low numerical rank. …”
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Recognition of Symbolic Gestures Using Depth Information by Hasan Mahmud, Md. Kamrul Hasan, Abdullah-Al-Tariq, Md. Hasanul Kabir, M. A. Mottalib

“…We have applied Scale-Invariant Feature Transform (SIFT) algorithm which takes the generated depth silhouettes as input and produces robust feature descriptors as output. …”
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ARCHIMEDES: Active Reasoning Conducted with Heterogeneous Information Monitors for Evading Dangers and Extended Surveillance by Simon Schoenbeck, Ugur Kuter

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IMAGE PROCESSING MODELS AND METHODS RESEARCH AND WAYS OF IMPROVING MARKER RECOGNITION TECHNOLOGIES IN ADDED REALITY SYSTEMS by Nataliia Bolohova, Igor Ruban

“…This is supported by algorithms of machine learning. You can also notice that the SIFT calculation works much faster than fractal texture analysis. …”
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WEIGHTED Decoding of Cyclic codes using quantized SIGNAL DEMODULATOR on PM signals by N. A. Salas, A. E. Korolev, V. K. Konopelko

“…A weighted iterative majority-logic decoding algorithm of cyclic codes with soft (quantized) detections of Phase-Modulating (PM) signals is analyzed. …”
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Vision-Based Grasping Method for Prosthetic Hands via Geometry and Symmetry Axis Recognition by Yi Zhang, Yanwei Xie, Qian Zhao, Xiaolei Xu, Hua Deng, Nianen Yi

“…Then, target object images are captured using binocular depth cameras, and the YOLO algorithm is employed for object detection. The SIFT algorithm is applied to extract the object’s symmetry axis, thereby determining the optimal grasp point and initial hand posture. …”
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Method of automatic coregistration of digital remote sensing images from different sources by A.N. Borisov, V.V. Myasnikov, V.V. Sergeev

“…To achieve a universal and robust solution in the latter stages, the best-known algorithms were compared: SIFT, SAR-SIFT, RIFT, and the trainable RoMa. …”
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Comprehensive empirical evaluation of feature extractors in computer vision by Murat ISIK

“…Utilizing the Image Matching Challenge Photo Tourism 2020 dataset, which includes over 1.5 million images, the study identifies the FAST algorithm as the most efficient detector when paired with the ORB descriptor and Brute-Force (BF) matcher, offering the fastest feature extraction and matching process. …”
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Deep Unified Model For Face Recognition Based on Convolution Neural Network and Edge Computing by Muhammad Zeeshan Khan, Saad Harous, Saleet Ul Hassan, Muhammad Usman Ghani Khan, Razi Iqbal, Shahid Mumtaz

“…Usually, for face recognition, scale-invariant feature transforms (SIFT) and speeded up robust features (SURF) have been used by the research community. …”
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Research on a Surface Roughness Measurement Under ResNet-Based Roughness Classification and Light-Section With Seam-Driven Image Stitching (RCLS) by Huashen Guan, Qiushen Cai, Xiaobin Li, Guofu Sun

“…First, the images were classified with ResNet neural network, then stitched and enhanced by scale invariant feature transform (SIFT) and optimized random sample consensus (RANSAC) algorithm for the best visual effect. …”
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Utilizing Cross-Layer Information to Improve Performance in JPEG2000 Decoding by Hannes Persson, Anna Brunstrom, Tony Ottosson

“…Further, experimental results with images transmitted over a simulated wireless channel show that a simple decoding algorithm that utilizes soft information can give high gains in image quality compared to the standard hard-decision decoding.…”
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