监禁
发表于 2025-3-25 09:24:36
https://doi.org/10.1007/978-981-13-7025-0Airborne Lidar; Artificial Intelligence; Image Processing; Image Reconstruction; Imaging Systems; K-means
流动才波动
发表于 2025-3-25 14:50:18
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MELON
发表于 2025-3-25 18:18:51
Communications in Computer and Information Science383035.jpg
Locale
发表于 2025-3-25 22:12:23
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Exploit
发表于 2025-3-26 03:04:15
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delta-waves
发表于 2025-3-26 04:24:06
Anita Runge,Lieselotte Steinbrüggethe optimization of K - Means clustering algorithm in the UCI machine learning database data set Sentiment labelled sentences and Sentence experiments on Corpus show that the algorithm not only can get better clustering results, The clustering results have high stability.
IST
发表于 2025-3-26 09:30:59
Soil Property Surface Modeling Based on Ensemble Learning for Complex Landforms,curacy was 6.42%, 7.28%, 11.56% and 9.38% higher than that of Regression Kriging (RK), Bayesian Kriging (BK), Inverse Distance Weighting (IDW) and Ordinary Kriging (OK), respectively. (2) The HASMSP-EL can provide more details in the geographical boundary, which made the simulation results consisten
Chromatic
发表于 2025-3-26 13:44:29
Mapping the Distribution of Exotic Mangrove Species in Shenzhen Bay Using Worldview-2 Imagery,N) classifier and support vector machine (SVM) classifier were applied to spectral and textural features, and six mangrove species classification results were obtained. Considering the six classification results together, the distribution of Sonneratia was mapped based on the criteria that, for each
含水层
发表于 2025-3-26 17:55:59
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white-matter
发表于 2025-3-26 22:27:52
Soil Property Surface Modeling Based on Ensemble Learning for Complex Landforms,n of global interpolation model and poor adaptability, a high accuracy surface modeling for soil property based on ensemble learning and fusion geographical environment variables was proposed (HASMSP-EL). The simulation accuracy of different interpolation methods was evaluated by using Mean Error (M