Suchergebnisse - "density-based spatial clustering of applications with noise"

Warship formation extraction and recognition based on density‐based spatial clustering of applications with noise and improved convolutional neural network von He, Haotian, Wu, Ling, Hu, Xianjun

“… ‐based spatial clustering of applications with noise (DBSCAN) method based on Gaussian kernel to extract formation targets …”
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Use Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Algorithm to Identify Galaxy Cluster Members von Zhang, Mingrui

“… Classification of galaxies into clusters is an urgent subject. How do we classify some observed galaxy data points as clusters …”
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A Radar-Based Human Activity Recognition Using a Novel 3-D Point Cloud Classifier von Yu, Zheqi, Taha, Ahmad, Taylor, William, Zahid, Adnan, Rajab, Khalid, Heidari, Hadi, Imran, Muhammad Ali, Abbasi, Qammer H.

“… This article provides a new benchmark dataset for 3-D point cloud classification in which the manually labeled human activity data exceeds 100 point clouds per …”
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A novel super-resolution microscopy platform for cutaneous alpha-synuclein detection in Parkinson’s disease von Sade, Ofir, Fischel, Daphna, Barak-Broner, Noa, Halevi, Shir, Gottfried, Irit, Bar-On, Dana, Sachs, Stefan, Mirelman, Anat, Thaler, Avner, Gour, Aviv, Kestenbaum, Meir, Gana Weisz, Mali, Anis, Saar, Soto, Claudio, Roitman, Melanie Shanie, Shahar, Shimon, Doppler, Kathrin, Sauer, Markus, Giladi, Nir, Lev, Nirit, Alcalay, Roy N., Hassin-Baer, Sharon, Ashery, Uri

“… Alpha-synuclein (aSyn) aggregates in the central nervous system are the main pathological hallmark of Parkinson’s disease (PD). ASyn aggregates have also been …”
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Detection of Random Body Movements Using Clustering-Based Methods in Bioradar Systems von Rouco, André, Silva, Filipe, Soares, Beatriz, Albuquerque, Daniel, Gouveia, Carolina, Brás, Susana, Pinho, Pedro

“… To address this challenge, this work proposes a solution based on the Density-Based Spatial Clustering of Applications with Noise (DBScan …”
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Prediction of Heart Disease by Optimized Distance and Density-Based Clustering von Sonawane, Ritesh, D.Patil, Hitendra

“… Prediction of cardiovascular disease is considered as one of the most significant subjects in the section of clinical data analysis …”
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Do Cognitive Subtypes Exist in People at Clinical High Risk for Psychosis? Results From the EU-GEI Study von Gifford, George, Avila, Alessia, Kempton, Matthew J, Fusar-Poli, Paolo, McCutcheon, Robert A, Coutts, Fiona, Tognin, Stefania, Valmaggia, Lucia, de Haan, Lieuwe, van der Gaag, Mark, Nelson, Barnaby, Pantelis, Christos, Riecher-Rössler, Anita, Bressan, Rodrigo, Barrantes-Vidal, Neus, Krebs, Marie-Odile, Glenthøj, Birte, Ruhrmann, Stephan, Sachs, Gabriele, Rutten, Bart P F, van Os, Jim, EU-GEI High Risk Study, McGuire, Philip

“… We explored whether an underlying cluster structure was present in the cognition data. Clustering of cognition data was performed using k-means clustering and density-based spatial clustering of applications with noise …”
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Fuzzy C-Means clustering algorithm for data with unequal cluster sizes and contaminated with noise and outliers: Review and development von Askari, Salar

“… •RFCM algorithm removes drawbacks of the FCM algorithm.•RFCM algorithm eliminates interactions among clusters.•RFCM algorithm is suitable for data highly …”
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A cluster-based ensemble approach for congenital heart disease prediction von Kaur, Ishleen, Ahmad, Tanvir

“… ). Although CHD risk factors have been the subject of numerous studies, their propensity to cause CHD has not been …”
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Non-Contact Heart Rate Variability Monitoring with FMCW Radar via a Novel Signal Processing Algorithm von Cui, Guangyu, Wang, Yujie, Zhang, Xinyi, Li, Jiale, Liu, Xinfeng, Li, Bijie, Wang, Jiayi, Zhang, Quan

“… (Density-Based Spatial Clustering of Applications with Noise) clustering techniques. Second, we established separate phase-based mathematical …”
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LDD-Track: An energy-efficient deep reinforcement learning framework for multi-subject tracking in mobile crowdsensing von Parhizi, Erfan, Esmaeilyfard, Rasool, Javidan, Reza

“… tracking framework that integrates Long Short-Term Memory (LSTM) networks with an adaptive attention mechanism, Density-Based Spatial Clustering of Applications with Noise (DBSCAN …”
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A comparative analysis of DBSCAN, K-means, and quadratic variation algorithms for automatic identification of swallows from swallowing accelerometry signals von Dudik, Joshua M., Kurosu, Atsuko, Coyle, James L., Sejdić, Ervin

“… : In this paper, we comparatively analyze the density-based spatial clustering of applications with noise algorithm (DBSCAN …”
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A framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data von Hu, Sheng, He, Zhanjun, Wu, Liang, Yin, Li, Xu, Yongyang, Cui, Haifu

“… Many studies are in an effort to explore urban spatial structure, and urban functional regions have become the subject of increasing attention among planners, engineers and public officials …”
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Detection of Outliers and Extreme Events of Ground Level Particulate Matter Using DBSCAN Algorithm with Local Parameters von Aslan, Meryem Ezgi, Onut, Semih

“… (particles smaller than or equal to 10 μm in diameter) data using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The results show the effectiveness of the method to identify noise and extreme events …”
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Extracting Symptoms of Complex Conditions From Online Discourse (Subreddit to Symptomatology): Lexicon-Based Approach von Hossain, Bushra, Preum, Sarah M, Rabbi, Md Fazle, Ara, Rifat, Ali, Mohammed Eunus

“… Millions of people affected with complex medical conditions with diverse symptoms often turn to online discourse to share their experiences. While some studies …”
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Replay-Based Incremental Learning Framework for Gesture Recognition Overcoming the Time-Varying Characteristics of sEMG Signals von Zhang, Xingguo, Li, Tengfei, Sun, Maoxun, Zhang, Lei, Zhang, Cheng, Zhang, Yue

“… % from eight subjects, which is significantly better than that of cross-day analysis. The density-based spatial clustering of applications with noise (DBSCAN …”
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Clustering Uncertain Data Objects Using Jeffreys-Divergence and Maximum Bipartite Matching Based Similarity Measure von Sharma, Krishna Kumar, Seal, Ayan, Yazidi, Anis, Selamat, Ali, Krejcar, Ondrej

“… In recent years, uncertain data clustering has become the subject of active research in many fields, for example, pattern recognition, and machine learning …”
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HDPM: An Effective Heart Disease Prediction Model for a Clinical Decision Support System von Fitriyani, Norma Latif, Syafrudin, Muhammad, Alfian, Ganjar, Rhee, Jongtae

“… This study proposes an effective heart disease prediction model (HDPM) for a CDSS which consists of Density-Based Spatial Clustering of Applications with Noise (DBSCAN …”
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The detection of low-rate DoS attacks using the SADBSCAN algorithm von Tang, Dan, Zhang, Siqi, Chen, Jingwen, Wang, Xiyin

“… They usually show a high false negative rate and are only applicable to small-scale data. We propose a new low-rate DoS attack detection scheme based on the self-adaptive density-based spatial clustering of applications with noise (SADBSCAN) algorithm …”
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Multi-verse optimizer for thermal error modeling approach of spindle system based on thermal image von Han, Yue, Deng, Xiaolei, Chen, Yushen, Fang, Chengzhi, Zhang, Wanjun, Chen, Yong, Wang, Jianchen

“… Since the spindle thermal error of CNC machine tools has a significant impact on machining precision, this paper introduces a unique approach for modeling …”
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