Handbook on Computer Learning and Intelligence

2022 ◽  
Author(s):  
Plamen Parvanov Angelov
Keyword(s):  
Computer Learning

A Human/Computer Learning Network to Improve Biodiversity Conservation and Research

AI Magazine ◽  
2012 ◽  
Vol 34 (1) ◽  
pp. 10 ◽  
Author(s):  
Steve Kelling ◽  
Jeff Gerbracht ◽  
Daniel Fink ◽  
Carl Lagoze ◽  
Weng-Keen Wong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Feedback Loop ◽  
Human Computation ◽  
Computational Power ◽  
Learning Networks ◽  
Learning Network ◽  
Computer Learning ◽  
The Individual ◽  
Citizen Science Project

In this paper we describe eBird, a citizen-science project that takes advantage of the human observational capacity to identify birds to species, which is then used to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human computation and mechanical computation. We call this a Human-Computer Learning Network, whose core is an active learning feedback loop between humans and machines that dramatically improves the quality of both, and thereby continually improves the effectiveness of the network as a whole. In this paper we explore how Human-Computer Learning Networks can leverage the contributions of a broad recruitment of human observers and processes their contributed data with Artificial Intelligence algorithms leading to a computational power that far exceeds the sum of the individual parts.

scholarly journals Computer learning evaluation with pre-test and post-test in preclinical education

2013 ◽  
Vol 7 (1) ◽  
pp. 61
Author(s):  
Phakakrong Samrejrongroj ◽  
Anchern Krikongjit ◽  
Nitchatorn Sungsirin ◽  
Vanich Vanapruks
Keyword(s):  
Computer Learning ◽  
Learning Evaluation ◽  
Post Test

A Visit to Professor Cram: Attractive Computer Learning

1983 ◽  
Vol 34 (3) ◽  
pp. 358
Author(s):  
Lynn J. Breininger ◽  
Stephen Portch
Keyword(s):  
Computer Learning

Handbook on Computer Learning and Intelligence

10.1142/12498 ◽  
2021 ◽  
Author(s):  
Plamen Parvanov Angelov
Keyword(s):  
Computer Learning

How Games Improve Language in People With Language Dysfunctions

2020 ◽  
pp. 1489-1505
Author(s):  
Robert Wahlstedt
Keyword(s):  
Natural Language ◽  
Hard Of Hearing ◽  
Learning Algorithm ◽  
Speech Pathology ◽  
Biological Processes ◽  
Biologically Inspired ◽  
Computer Learning ◽  
Facial Muscles ◽  
Natural Sound ◽  
Existing Data

Many people as they age face a greater challenge of muscular dexterity around their facial muscles. This results in difficulty producing certain sounds, and sometimes the problem is so severe that they are unintelligible. People who could benefit from the methods in this chapter are those who are hard of hearing and do not have feedback readily accessible and people with ALS. This chapter describes a method that uses a computer learning algorithm that predicts what people are about to say based on earlier content and learns what the natural sound of their voice sounds like. This chapter illustrates speech trajectory and voice shaping. Clear Audio is a biologically inspired framework for studying natural language. Like the story behind Jurassic Park, Clear Audio attempts to make predictions about data from existing data, inspired by biological processes. Its main goal is to give feedback for speech pathology purposes.

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