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Pattern Recognition and Image Analysis
ISSN 1054-6618 (Print) ISSN 1555-6212 (Online)
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关键字 Euclidean space algebraic approach classification clustering computer vision data mining deep learning edge detection face recognition feature extraction image analysis image processing image segmentation machine learning neural networks object detection pattern recognition recognition segmentation support vector machine wavelet transform
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关键字 Euclidean space algebraic approach classification clustering computer vision data mining deep learning edge detection face recognition feature extraction image analysis image processing image segmentation machine learning neural networks object detection pattern recognition recognition segmentation support vector machine wavelet transform
首页 > 检索 > 作者的详细信息

作者的详细信息

Rudakov, K. V.

期 栏目 标题 文件
卷 26, 编号 2 (2016) Mathematical Method in Pattern Recognition On metric spaces arising during formalization of recognition and classification problems. Part 1: Properties of compactness
卷 26, 编号 3 (2016) Methematical Method in Pattern Recognition On metric spaces arising during formalization of problems of recognition and classification. Part 2: Density properties
卷 27, 编号 1 (2017) Mathematical Method in Pattern Recognition Combinatorial analysis of the solvability properties of the problems of recognition and completeness of algorithmic models. Part 1: Factorization approach
卷 27, 编号 2 (2017) Mathematical Method in Pattern Recognition Combinatorial analysis of the solvability properties of the problems of recognition and completeness of algorithmic models. Part 2: Metric approach within the framework of the theory of classification of feature values
卷 29, 编号 3 (2019) General Problems, Methodology and Principles of Pattern Recognition and Image Analysis Mathematical Foundations for Processing High Data Volume, Machine Learning, and Artificial Intelligence
卷 29, 编号 4 (2019) Applied Artificial Intelligence Systems. Knowledge-Based and Intelligence Systems On the Procedures of Generation of Numerical Features over Partitions of Sets of Objects in the Problem of Predicting Numerical Target Variables
 

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