Learning by precedents based on the analysis of the features properties by V. V. Krasnoproshin, V. G. Rodchanka

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ALGORITHM OF PREPARATION OF THE TRAINING SAMPLE USING 3D-FACE MODELING by D. I. Samal, I. I. Frolov

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Study of the possibility of using an artificial neural network to recognize and assess the contribution of individual radionuclides to the total beta spectrum by V. S. Repin

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End-to-End Horse Gait Classification in Uncontrolled Environments Using Inertial Sensors by Mahaut Gerard, Sandrine Hanne-Poujade, Guillaume Dubois, Henry Chateau, Neila Mezghani

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Detecting Long-Term Spatiotemporal Dynamics of Urban Green Spaces with Training Sample Migration Method by Mengyao Wang, Pan Li, Chunyu Wang, Wei Chen, Zhongen Niu, Na Zeng, Xingxing Han, Xinchao Sun

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Comparative analysis of the performance of selected machine learning algorithms depending on the size of the training sample by Kupidura Przemysław, Kępa Agnieszka, Krawczyk Piotr

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Default Priors in a Zero-Inflated Poisson Distribution: Intrinsic Versus Integral Priors by Junhyeok Hong, Kipum Kim, Seong W. Kim

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Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

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Deep learning-based detection and evaluation of building changes in rail transit protection zones by Cai Jia, Long Zhao, Chengyang Qian, Yu Zhang, Zini Cao, Xiaoqiang Zhu

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Artificial Neural Network in the CATS Training System by Yu. V. Popova

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THE SOLUTION OF THE APPROXIMATION PROBLEM OF NONLINEAR DEPENDANCES USING ARTIFICIAL NEURAL NETWORKS by V. N. Ageyev

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Superpixel guided spectral-spatial feature extraction and weighted feature fusion for hyperspectral image classification with limited training samples by Yao Li, Liyi Zhang, Lei Chen, Yunpeng Ma

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Enhancing Cropland Mapping with Spatial Super-Resolution Reconstruction by Optimizing Training Samples for Image Super-Resolution Models by Xiaofeng Jia, Xinyan Li, Zirui Wang, Zhen Hao, Dong Ren, Hui Liu, Yun Du, Feng Ling

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Automatic training sample collection utilizing multi-source land cover products and time-series Sentinel-2 images by Yanzhao Wang, Yonghua Sun, Xuyue Cao, Yihan Wang, Wangkuan Zhang, Xinglu Cheng, Ruozeng Wang, Jinkun Zong

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The impact of fractional cover distribution in training samples on the accuracy of fractional cover estimation: a model-based evaluation by Rujia Wang, Chen Shi

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Kernelised reference‐wise metric learning by Meng Wu, Kai Luo, Daijin Li, Jun Zhou

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IMPACT OF IMAGE PRE-PROCESSING ON QUALITY OF TRAINING NEURAL NETWORK FOR RECOGNITION by Nikita A. Lagunov, Oksana S. Mezentseva

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