Radio frequency based distributed system for noncooperative UAV classification and positioning by Chaozheng Xue, Tao Li, Yongzhao Li

“…Specifically, three passive receivers are arranged in different locations to receive RF signals. …”
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ORDINAL LOGISTIC REGRESSION MODEL AND CLASSIFICATION TREE ON ORDINAL RESPONSE DATA by Jajang Jajang, Nunung Nurhayati, Suci Jena Mufida

“…The HDI data is categorized into three levels, namely very high, high, and moderate. …”
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Triple Graph Convolutional Network for Hyperspectral Image Feature Fusion and Classification by Maryam Imani, Daniele Cerra

“…These graphs are processed using graph convolutional networks, and their results are fused using a cross-attention mechanism. The experiments on three hyperspectral benchmark datasets show that the GF2 network has high classification performance compared to state-of-the-art methods, while imposing a reasonable number of learnable parameters.…”
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FAHPBEP: A Fuzzy Analytic Hierarchy Process Framework in Text Classification by Razieh Asgarnezhad, Sayed Monadjemi, MohammadReza Soltanaghaei

“…This research probes to investigate the performance of pre-processing for the Sentiment Classification problem on three popular datasets. We suggest a high-performance framework to enhance classification performance.  …”
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Efficient Classification and Rapid Processing of Big Data in Power Distribution Networks by Luan Ning, Cheng Li, Wang Dingji, Wang Shuaimei

“…We use the fast Fourier transform for autocorrelation coefficients calculation to define the repetitive score, and the sparse score and increasing/decreasing score are also defined for evaluating three patterns. Three different dimension reduction methods, viz. …”
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Commodity Image Classification Based on Improved Bag-of-Visual-Words Model by Huadong Sun, Xu Zhang, Xiaowei Han, Xuesong Jin, Zhijie Zhao

“…Experimental results show that the three aspects of improvement to the BoVW model are complementary, while compared with the traditional BoVW and the BoVW adopting SURF + SPM, the classification accuracy of the improved BoVW is increased by 3.60% and 2.33%, respectively.…”
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Clinical and dermoscopic assessment of angiosarcoma: a diagnostic classification for early detection by Vincenzo De Giorgi, Biancamaria Zuccaro, Giovanni Cecchi, Gabriella Perillo, Ignazio Stanganelli, Piero Covarelli

“…This study aimed to evaluate the clinical and dermatoscopic features of CMA in order to create a classification that can be useful in the early diagnosis of this rare but fearful tumor. …”
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Nasal correction in nasomaxillary hypoplasia (Binder’s syndrome): An optimised classification and treatment by Venkata Ramana Yamani, Shakuntala Ghosh, Shreekumar Tirunagari

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Application of Machine Learning in Fault Detection And Classification in Power Transmission Lines by Michel Evariste Tshodi, Nathanael Kasoro, Freddy Keredjim, ALbert Ntumba Nkongolo, Jean-Jacques Katshitshi Matondo, Paul Mbuyi Balowe, Laurent Kitoko

“…Six fault categories were found in the dataset: No-Fault (2365 occurrences), Line A Line B to Ground Fault (1134 occurrences), Three-Phase with Ground (1133 occurrences), Line-to-Line AB (1129 occurrences), Three-Phase (1096 occurrences) and finally Line-to-Line with Ground BC (1004 occurrences).…”
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Classification of Elliptic Cubic Curves Over The Finite Field of Order Nineteen by Baghdad Science Journal

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Hardwood riparian forests in northern Iberian Peninsula: classification and diversity patterns by Idoia Biurrun, Jokin Belmonte, Irati Sanz-Zubizarreta, Juan Antonio Campos

“…In this study we aim to 1) confirm their presence in small rivers of northern Spain, 2) revise their classification at association level, and discuss it at alliance level, 3) evaluate their diversity patterns and ecological preferences. …”
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Caesarean Section in Peru: Analysis of Trends Using the Robson Classification System. by Vilma Tapia, Ana Pilar Betran, Gustavo F Gonzales

“…The aims of the present study were to conduct an analysis in the three Peruvian geographical regions to assess levels and trends of delivery by caesarean section using the Robson classification for caesarean section, identify the groups of women with highest caesarean section rates and assess variation of maternal and perinatal outcomes according to caesarean section levels in each group over time.…”
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Non-Invasive Painting Pigment Classification Through Supervised Machine Learning by Michal Piotr Markowski, Solongo Gansukh, Mateusz Madry, Robert Borowiec, Jaroslaw Rogoz, Boguslaw Szczupak

“…This study demonstrates that accurate pigment classification can be achieved with a minimal set of three illumination types, offering a practical and cost-effective alternative to hyperspectral imaging in real-world conservation practice. …”
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Classification and functional repair and reconstruction of lip and perilabial defects following oncosurgery by CHEN Weiliang

“…Currently, there is a lack of clear classification and principles for repairing and reconstructing the lip and perilabial defects after lip tumor resection surgery. …”
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Application of bilateral fusion model based on CNN in hyperspectral image classification by Hongmin GAO, Xueying CAO, Yao YANG, Zaijun HUA, Chenming LI

“…Aiming at the issues of decreasing spatial resolution and feature loss caused by pooling operation in depth CNN-based hyperspectral image classification algorithm,a bilateral fusion block network （DFBN）composed of bilateral fusion blocks was designed.The upper structure of bilateral fusion block was constituted by 1×1 convolution and hyperlink,which was used to transfer local spatial characteristics.The lower structure was constituted by pooling layer,convolutional layer,deconvolution layer and upsampling to enhance the characteristics of efficient discrimination.Experimental results on three benchmark hyperspectral image data sets illustrate that the model is superior to other similar classification models.…”
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Pesticide Mode of Action Classification: Understanding Resistance Action Committees (RACs) by Emily C. Kraus, Brett Bultemeier

“…To this end, it defines the development and goals of the three Resistance Action Committees for insecticides (IRAC), herbicides (HRAC), and fungicides (FRAC) and describes each group’s pesticide mode of action classification scheme. …”
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Pesticide Mode of Action Classification: Understanding Resistance Action Committees (RACs) by Emily C. Kraus, Brett Bultemeier

“…To this end, it defines the development and goals of the three Resistance Action Committees for insecticides (IRAC), herbicides (HRAC), and fungicides (FRAC) and describes each group’s pesticide mode of action classification scheme. …”
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Deep learning empowered sensor fusion boosts infant movement classification by Tomas Kulvicius, Dajie Zhang, Luise Poustka, Sven Bölte, Lennart Jahn, Sarah Flügge, Marc Kraft, Markus Zweckstetter, Karin Nielsen-Saines, Florentin Wörgötter, Peter B. Marschik

“…Results The performance of the three-sensor fusion (classification accuracy of 94.5%) is significantly higher than that of any single modality evaluated. …”
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Pediatric heart failure classification based on left ventricular ejection fraction by Shan Huang, Xue Xiang, Xu Zhu, Jie Tian, Bo Pan, Min Zheng

“…Abstract Left ventricle ejection fraction (LVEF) is still not well acknowledged in classification of pediatric heart failure (PHF). We categorized PHF according to LVEF and aimed to determine the role of LVEF in PHF classification. …”
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Research on network traffic classification based on machine learning and deep learning by Yue GU, Dan LI, Kaihui GAO

“…With the continuous development of Internet technology and the continuous expansion of network scale, there are many different types of applications , and various new applications have endlessly emerged.In order to ensure the quality of service (QoS) and ensure network security, accurate and fast traffic classification is an urgent problem for both operators and network managers.Firstly, the problem definition and performance metrics of network traffic classification were given.Then, the traffic classification methods based on machine learning and deep learning were introduced respectively, the advantages and disadvantages of these methods were analyzed, and the existing problems were expounded.Next, the related work by focusing on the three problems encountered elaborated and analyzed in traffic classification when considering online deployment: dataset, zero-day application identification and the cost of online deployment, and further discusses the challenges faced by the current network traffic classification researches.Finally, the next research direction of network traffic classification was prospected.…”
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