Introduction: architectural identities of European peripheries

Brouwer, Petra; Jõekalda, Kristina

doi:10.1080/13602365.2020.1851542

Cited by 1 publication

(1 citation statement)

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“…The grouping algorithm divides data objects into multiple parts according to the characteristics of the data to reduce the external similarity of each category and increase the internal similarity of each element. While both grouping and adaptation are data isolation, grouping is an unmanaged learning process, while isolation is a managed training process [ 23 ]. The isolation algorithm must first understand the structural characteristics of the data and classify according to the characteristics of the data structure and at the same time integrate the algorithm to find the characteristics of the data structure.…”

Section: Building Image Feature Extraction Methodsmentioning

confidence: 99%

Building Image Feature Extraction Using Data Mining Technology

Deng

Xing

Cai

2022

Computational Intelligence and Neuroscience

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At present, data mining technology is continuously researched in science and application. With the rapid development of remote sensing satellite industry, especially the launch of remote sensing satellites with high-resolution sensors, the amount of information obtained from remote sensing images has increased dramatically, which has largely promoted the application of remote sensing data in various industries. This technique mines useable information from less complete and accurate data while ensuring low program complexity. In order to determine the impact of data mining techniques on feature extraction of graphic images, this paper explores the relevant steps in the image recognition process, especially the image preenhancement and image extraction processes. This paper develops a preliminary set of relevant data and investigates two different extraction methods based on the availability or absence of nursing information. Aiming at the advantages and disadvantages of the two house extraction methods, this work discusses how to effectively integrate remote sensing data. It uses different data sources to describe different characteristics of buildings, analyzes and extracts effective information, and finally derives building information. The research results show that, using the SVM algorithm in data mining for image feature extraction, in the verified filtering window, the accuracy can be effectively improved by about 20%. Buildings are important objects in high-resolution remote sensing images, and their feature extraction and recognition technology is of great significance in many fields such as digital city construction, urban planning, and military reconnaissance.

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Section: Building Image Feature Extraction Methodsmentioning

confidence: 99%