Literature DB >> 4045580

Detection and identification: how are they related?

J P Thomas.   

Abstract

Detection and identification are described as using the same base of sensory information but applying different decision processes. Consistent with this view, there is no evidence of different sensory cutoffs for the two tasks, and accuracies in the two tasks vary as a function of stimulus strength in closely related fashion. Identification accuracy also depends on the extent to which stimuli are processed independently, and the quantitative relationship between identification and detection can be used to estimate the degree of independence.

Mesh:

Year:  1985        PMID: 4045580     DOI: 10.1364/josaa.2.001457

Source DB:  PubMed          Journal:  J Opt Soc Am A        ISSN: 0740-3232            Impact factor:   2.129


  11 in total

1.  Hemispheric differences are found in the identification, but not the detection, of low versus high spatial frequencies.

Authors:  F L Kitterle; S Christman; J B Hellige
Journal:  Percept Psychophys       Date:  1990-10

2.  Visual field effects in the discrimination of sine-wave gratings.

Authors:  F L Kitterle; L M Selig
Journal:  Percept Psychophys       Date:  1991-07

3.  Detection and discrimination of first- and second-order motion in patients with unilateral brain damage.

Authors:  M W Greenlee; A T Smith
Journal:  J Neurosci       Date:  1997-01-15       Impact factor: 6.167

4.  The statistical analysis of concurrent detection ratings.

Authors:  T D Wickens; L A Olzak
Journal:  Percept Psychophys       Date:  1989-06

5.  Definition of thresholds for stereoscopic depth.

Authors:  M Fahle; S Henke-Fahle; J Harris
Journal:  Br J Ophthalmol       Date:  1994-07       Impact factor: 4.638

6.  An evaluation of psychophysical models of auditory change perception.

Authors:  Christophe Micheyl; Christian Kaernbach; Laurent Demany
Journal:  Psychol Rev       Date:  2008-10       Impact factor: 8.934

7.  Detection and identification of crowded mirror-image letters in normal peripheral vision.

Authors:  Susana T L Chung
Journal:  Vision Res       Date:  2009-12-02       Impact factor: 1.886

8.  Stochastic model for detection of signals in noise.

Authors:  Stanley A Klein; Dennis M Levi
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2009-11       Impact factor: 2.129

Review 9.  Crowding--an essential bottleneck for object recognition: a mini-review.

Authors:  Dennis M Levi
Journal:  Vision Res       Date:  2008-01-28       Impact factor: 1.886

10.  Cry-based infant pathology classification using GMMs.

Authors:  Hesam Farsaie Alaie; Lina Abou-Abbas; Chakib Tadj
Journal:  Speech Commun       Date:  2016-03       Impact factor: 2.017

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