Volare alto con l'Intelligenza Artificiale

JOHN MCCARTHY, computer scientist at Stanford University, first coined the term "artificial intelligence” in 1955, defining it as, "the science and engineering of making intelligent machines, especially intelligent computer programs.” Machines are intelligent when they can replicate human...

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Autor principal:	Marc M. Delgado
Formato:	article
Lenguaje:	EN IT
Publicado:	mediaGEO soc. coop. 2021
Materias:	Intelligenza Artificiale machine learning deep learning computer vision mapping immagini satellitari Cartography GA101-1776 Cadastral mapping GA109.5
Acceso en línea:	https://doaj.org/article/3de4d0d135f74f7081738b52bf3e8b9d
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id	oai:doaj.org-article:3de4d0d135f74f7081738b52bf3e8b9d
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spelling	oai:doaj.org-article:3de4d0d135f74f7081738b52bf3e8b9d2021-11-09T17:41:57ZVolare alto con l'Intelligenza Artificiale10.48258/geo.v24i5.17531128-81322283-5687https://doaj.org/article/3de4d0d135f74f7081738b52bf3e8b9d2021-01-01T00:00:00Zhttps://www.mediageo.it/ojs/index.php/GEOmedia/article/view/1753https://doaj.org/toc/1128-8132https://doaj.org/toc/2283-5687 JOHN MCCARTHY, computer scientist at Stanford University, first coined the term "artificial intelligence” in 1955, defining it as, "the science and engineering of making intelligent machines, especially intelligent computer programs.” Machines are intelligent when they can replicate human cognitive skills such as forming categories, recognizing patterns, and solving problems. For machines to achieve artificial intelligence, computer programmers must create algorithms that can scan and organize input data to train and teach the machines to perform tasks. This method is called machine learning, the most basic of all AI techniques. Several other AI methods have since been developed, including neural network, a process that mimics how the human brain learns by using interconnected nodes to process data. Its more sophisticated version is called deep learning, which uses multiple layers of neural networks so that computers can analyze bigger datasets. With the advent of big geospatial data, there are far more inputs for AI machines to train on and improve their accuracy. And due to AI's ability to handle big datasets such as imagery, computer vision is currently one of the hottest geospatial applications. With computer vision technology, machines can be taught to "see” real-world objects from images, thus allowing companies like Mapillary to identify roads from street photos, Ecopia to extract built-up areas from satellite imagery, and VOXELGRID to recognize construction materials from a point cloud. Marc M. DelgadomediaGEO soc. coop.articleIntelligenza Artificialemachine learningdeep learningcomputer visionmappingimmagini satellitariCartographyGA101-1776Cadastral mappingGA109.5ENITGEOmedia, Vol 24, Iss 5 (2021)
institution	DOAJ
collection	DOAJ
language	EN IT
topic	Intelligenza Artificiale machine learning deep learning computer vision mapping immagini satellitari Cartography GA101-1776 Cadastral mapping GA109.5
spellingShingle	Intelligenza Artificiale machine learning deep learning computer vision mapping immagini satellitari Cartography GA101-1776 Cadastral mapping GA109.5 Marc M. Delgado Volare alto con l'Intelligenza Artificiale
description	JOHN MCCARTHY, computer scientist at Stanford University, first coined the term "artificial intelligence” in 1955, defining it as, "the science and engineering of making intelligent machines, especially intelligent computer programs.” Machines are intelligent when they can replicate human cognitive skills such as forming categories, recognizing patterns, and solving problems. For machines to achieve artificial intelligence, computer programmers must create algorithms that can scan and organize input data to train and teach the machines to perform tasks. This method is called machine learning, the most basic of all AI techniques. Several other AI methods have since been developed, including neural network, a process that mimics how the human brain learns by using interconnected nodes to process data. Its more sophisticated version is called deep learning, which uses multiple layers of neural networks so that computers can analyze bigger datasets. With the advent of big geospatial data, there are far more inputs for AI machines to train on and improve their accuracy. And due to AI's ability to handle big datasets such as imagery, computer vision is currently one of the hottest geospatial applications. With computer vision technology, machines can be taught to "see” real-world objects from images, thus allowing companies like Mapillary to identify roads from street photos, Ecopia to extract built-up areas from satellite imagery, and VOXELGRID to recognize construction materials from a point cloud.
format	article
author	Marc M. Delgado
author_facet	Marc M. Delgado
author_sort	Marc M. Delgado
title	Volare alto con l'Intelligenza Artificiale
title_short	Volare alto con l'Intelligenza Artificiale
title_full	Volare alto con l'Intelligenza Artificiale
title_fullStr	Volare alto con l'Intelligenza Artificiale
title_full_unstemmed	Volare alto con l'Intelligenza Artificiale
title_sort	volare alto con l'intelligenza artificiale
publisher	mediaGEO soc. coop.
publishDate	2021
url	https://doaj.org/article/3de4d0d135f74f7081738b52bf3e8b9d
work_keys_str_mv	AT marcmdelgado volarealtoconlintelligenzaartificiale
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Volare alto con l'Intelligenza Artificiale

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