The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Soft Computing Techniques for Human-Computer Interaction
|
|
Author(s): Oscar Déniz (Universidad de Castilla-La Mancha, Spain), Gloria Bueno (Universidad de Castilla-La Mancha, Spain), Modesto Castrillón (Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería, Spain), Javier Lorenzo (Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería, Spain), L. Antón (Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería, Spain)and M. Hernández (Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería, Spain)
Copyright: 2010
Pages: 15
Source title:
Soft Computing Methods for Practical Environment Solutions: Techniques and Studies
Source Author(s)/Editor(s): Marcos Gestal Pose (University of A Coruna, Spain)and Daniel Rivero Cebrián (University of A Coruna, Spain)
DOI: 10.4018/978-1-61520-893-7.ch003
Purchase
|
Abstract
Soft computing aims at using tricks or shortcuts that do not provide optimal solutions but useful approximations that can be computed at a reasonable cost. Such approximations often come in the form of heuristics and “rules of thumb.” Computer vision relies heavily on heuristics, being a simple example the detection of faces by detecting skin color. Another approach that may also be considered as heuristics is the use of inductive learning, where the idea is to emulate humans in the sense that achieving certain skills require gradual learning. Thus, we would not make an effort to articulate solutions as equations, rules or algorithms. The solution would instead be sought automatically by feeding the system with training examples that would allow it to classify new samples. This chapter describes two successful applications of such soft computing approaches in the field of human-computer interaction, showing how the clever use of heuristics and domain restrictions can help to find solutions for the most difficult problems in this field.
Related Content
|
Bhargav Naidu Matcha, Sivakumar Sivanesan, K. C. Ng, Se Yong Eh Noum, Aman Sharma.
© 2023.
60 pages.
|
|
Lavanya Sendhilvel, Kush Diwakar Desai, Simran Adake, Rachit Bisaria, Hemang Ghanshyambhai Vekariya.
© 2023.
15 pages.
|
|
Jayanthi Ganapathy, Purushothaman R., Ramya M., Joselyn Diana C..
© 2023.
14 pages.
|
|
Prince Rajak, Anjali Sagar Jangde, Govind P. Gupta.
© 2023.
14 pages.
|
|
Mustafa Eren Akpınar.
© 2023.
9 pages.
|
|
Sreekantha Desai Karanam, Krithin M., R. V. Kulkarni.
© 2023.
34 pages.
|
|
Omprakash Nayak, Tejaswini Pallapothala, Govind P. Gupta.
© 2023.
19 pages.
|
|
|