UOrtos: Methodology for Co-Registration and Subpixel Georeferencing of Satellite Imagery for Coastal Monitoring by Gonzalo Simarro, Daniel Calvete, Francesca Ribas, Yeray Castillo, Càrol Puig-Polo

“…The approach utilizes feature-based methods, cross-correlation, and RANSAC (RANdom SAmple Consensus) algorithms to accurately align images while avoiding outliers. …”
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Calculation Method of Phenotypic Traits for Tomato Canopy in Greenhouse Based on the Extraction of Branch Skeleton by Xiaodan Ma, Qiu Jiang, Haiou Guan, Lu Wang, Xia Wu

“…In addition, the DBSCAN clustering algorithm was applied to recognize individual leaf organs. …”
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Unsupervised Feature Selection With Ordinal Preserving Self-Representation by Jiangyan Dai, Yuqi Chen, Yugen Yi, Jining Bao, Lei Wang, Wei Zhou, Gang Lei

“…In this paper, we propose a novel unsupervised feature selection algorithm, namely ordinal preserving self-representation (OPSR) for image classification and clustering. …”
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Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History by Danping Wang, Kunyuan Hu, Lianbo Ma, Maowei He, Hanning Chen

“…A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH) is proposed. …”
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An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based Geomonitoring by Z. Wang, J. A. Butt, J. A. Butt, S. Huang, N. Meyer, T. Medić, A. Wieser

“…Our method comprises three main steps: (1) applying the Efficient-LoFTR algorithm to establish dense 2D pixel correspondences on RGB images across two epochs; (2) projecting 3D points from both epochs onto RGB images and establishing 3D point correspondences by matching the projected pixels with the established 2D correspondences; (3) clustering the point cloud of one epoch and refining the 3D point correspondences within each cluster to produce the final displacement vector fields. …”
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An Energy-Domain IR NUC Method Based on Unsupervised Learning by Ting Li, Xuefeng Lai, Sheng Liao, Yucheng Xia

“…The maximum change in the image corrected using the proposed algorithm was 1.29%.…”
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Information-extremе machine learning for object identification on the terrain by V. V. Moskalenko, A. H. Korobov

“…The article deals with the usage of a SURF local descriptor of key fragments to create a global descriptor BoF for objects of interest on terrain within task of recognition of armored technique in the controlled territory using images of air reconnaissance. The method of optimization of the input mathematical description of the information-extreme classifier trained on dataset, which consist of global descriptors BoF, is proposed. …”
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Urban pulse: measuring pace of life through public camera-based cadence analysis by Pei-Yu Ho, Ming-Kuang Chung, Ling-Jyh Chen

“…The Real-Time Image Collection Module autonomously gathers video streams from a network of public live cameras; the Pedestrian Feature Extraction Module employs the You Only Look Once version 7 (YOLOv7) model along with the Simple Online and Real-Time Tracking (SORT) algorithm to produce time series data of pedestrian characteristics; following this, the Pedestrian Cadence Estimation Module applies signal processing to these data to evaluate pedestrian cadence. …”
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Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

“…The review method includes an in-depth analysis of algorithm performance using key metrics such as accuracy, precision, recall, and F1 score across various datasets. …”
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Identification of Global Extended Pseudo Invariant Calibration Sites (EPICS) and Their Validation Using Radiometric Calibration Network (RadCalNet) by Juliana Fajardo Rueda, Larry Leigh, Cibele Teixeira Pinto

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SpatialKNifeY (SKNY): Extending from spatial domain to surrounding area to identify microenvironment features with single-cell spatial omics data. by Shunsuke A Sakai, Ryosuke Nomura, Satoi Nagasawa, SungGi Chi, Ayako Suzuki, Yutaka Suzuki, Mitsuho Imai, Yoshiaki Nakamura, Takayuki Yoshino, Shumpei Ishikawa, Katsuya Tsuchihara, Shun-Ichiro Kageyama, Riu Yamashita

“…Using spatial transcriptomic data from breast cancer, we applied the SKNY algorithm to identify tumor spatial domains, followed by clustering of the domains, trajectory estimation, and spatial extension to the tumor microenvironment (TME). …”
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Measurements and Characterization for Millimeter-Wave Massive MIMO Channel in High-Speed Railway Station Environment at 28 GHz by Shuangde Li, Yuanjian Liu, Leke Lin, Qi Sun

“…And they are processed by using the K-mean algorithm. In addition, propagation characteristics are simulated based on the improved ray tracing method of shooting and bouncing ray tracing/image (SBR/IM). …”
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Classification of Upper Bound Sequences of Local Fractional Metric Dimension of Rotationally Symmetric Hexagonal Planar Networks by Shahbaz Ali, Muhammad Khalid Mahmood, Fairouz Tchier, F. M. O. Tawfiq

“…In the field of computer science, metric dimensions are most useful in aspects such as image processing, navigation, pattern recognition, and integer programming problem. …”
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A Novel IKP-Based Biometric Recognition Using Mobile Phone Camera by Xue-Miao Xu, Xiao-Zheng Lai, Qiang Jin, Xue-Han Yuan, Sheng-Li Lai, Yan-Wen Lin, Jian-Wen Huang

“…Since IKP characteristics are captured by using mobile phone camera, the greatest challenge is that IKP images from the same hand have different illumination, posture, and background. …”
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Agricultural crop pattern mapping and change analysis at a sub-district level in South-eastern region, Bangladesh using Landsat satellite data from 2010 to 2019 by Biswajit Nath, Monir Hossain, Sahadeb Chandra Majumder

“…To overcome this, we have considered frequently used traditional unsupervised classifier, such as K-means clustering algorithm technique. This has been applied on 30m pixel Landsat satellite reflectance images to identify crop pattern of the study area using the ENVI 5.3 and ArcGIS 10.8 software’s, respectively. …”
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Machine-Learning-Based Integrated Mining Big Data and Multi-Dimensional Ore-Forming Prediction: A Case Study of Yanshan Iron Mine, Hebei, China by Yuhao Chen, Gongwen Wang, Nini Mou, Leilei Huang, Rong Mei, Mingyuan Zhang

“…The specific research contents and results are as follows: (1) This study collected and organized multi-source geoscience data for the Yanshan Iron Mine, including geological, geophysical, and remote sensing data, such as mine drilling data, centimeter-level drone image data, and high-spectral data of rocks and minerals, establishing a rich mine big data set. (2) SOM clustering analysis was performed on the elemental data of rock and mineral samples, identifying key elements positively correlated with iron as Mg, Al, Si, S, K, Ca, and Mn. …”
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An Efficient Cryptosystem for Video Surveillance in the Internet of Things Environment by Rafik Hamza, Alzubair Hassan, Teng Huang, Lishan Ke, Hongyang Yan

“…Finally, the proposed framework performs an efficient image encryption algorithm by employing a discrete fractional random transform (DFRT). …”
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Application of support vector machine system introducing multiple submodels in data mining by Weinan Tang

“…By introducing open-source tools such as OpenCV, image feature extraction can be performed on large-scale video data. …”
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Fuzzy Intelligence in Physical Immersion Teaching System Based on Digital Simulation Technology by Aihui Du

“…In addition, this study proposes a new algorithm based on the morphological features of geometric images, which combines the transformation detection method of cluster analysis to realize the intelligent processing of images. …”
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Automatic Extraction Method of Phenotypic Parameters for <i>Phoebe zhennan</i> Seedlings Based on 3D Point Cloud by Yang Zhou, Yikai Qi, Longbin Xiang

“…First, the processed point cloud image was aligned using the Sample Consensus Initial Aligment (SAC-IA) and Iterative Closest Point (ICP) algorithms to generate a three-dimensional model of the seedlings. …”
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