scholarly journals Calculation Efficiencies for Mean Numerosity

2018 ◽  
Vol 29 (11) ◽  
pp. 1824-1831 ◽  
Author(s):  
Joshua A. Solomon ◽  
Michael J. Morgan
Keyword(s):  
Present Experiment ◽  
Weber Fraction ◽  
Ideal Observer

Relative numerosity is traditionally studied using texture pairs. Observers must decide which member of each pair has the greater total number of texture elements. In the present experiment, textures were segregated into nonoverlapping “sectors” containing between zero and four elements, and our observers were asked to select the texture containing the greater average number of texture elements (per sector). If observers were more sensitive to total numerosity than average numerosity, their performance (quantified by the just-noticeable Weber fraction) should have been better when the two textures occupied the same number of sectors than when they occupied unequal numbers of sectors. However, we recorded Weber fractions between 11% and 13% for all observers in all conditions. This performance was comparable with an otherwise-ideal observer whose decisions were based on between three and five sectors in each texture. We conjecture that traditional numerosity discriminations are based on similarly small numbers of element clusters.

CNN performance dependence on linear image processing

2020 ◽  
Vol 2020 (10) ◽  
pp. 310-1-310-7
Author(s):  
Khalid Omer ◽  
Luca Caucci ◽  
Meredith Kupinski
Keyword(s):  
Image Processing ◽  
Texture Classification ◽  
Full Rank ◽  
Detection Performance ◽  
Ideal Observer ◽  
Training Data ◽  
Image Texture ◽  
Training Images ◽  
Analytic Expressions ◽  
Linear Compression

This work reports on convolutional neural network (CNN) performance on an image texture classification task as a function of linear image processing and number of training images. Detection performance of single and multi-layer CNNs (sCNN/mCNN) are compared to optimal observers. Performance is quantified by the area under the receiver operating characteristic (ROC) curve, also known as the AUC. For perfect detection AUC = 1.0 and AUC = 0.5 for guessing. The Ideal Observer (IO) maximizes AUC but is prohibitive in practice because it depends on high-dimensional image likelihoods. The IO performance is invariant to any fullrank, invertible linear image processing. This work demonstrates the existence of full-rank, invertible linear transforms that can degrade both sCNN and mCNN even in the limit of large quantities of training data. A subsequent invertible linear transform changes the images’ correlation structure again and can improve this AUC. Stationary textures sampled from zero mean and unequal covariance Gaussian distributions allow closed-form analytic expressions for the IO and optimal linear compression. Linear compression is a mitigation technique for high-dimension low sample size (HDLSS) applications. By definition, compression strictly decreases or maintains IO detection performance. For small quantities of training data, linear image compression prior to the sCNN architecture can increase AUC from 0.56 to 0.93. Results indicate an optimal compression ratio for CNN based on task difficulty, compression method, and number of training images.

Object Detection Using an Ideal Observer Model

2020 ◽  
Vol 2020 (16) ◽  
pp. 41-1-41-7
Author(s):  
Orit Skorka ◽  
Paul J. Kane
Keyword(s):  
Object Detection ◽  
Matched Filter ◽  
Image Sensors ◽  
Ideal Observer ◽  
Noise Power ◽  
Relative Evaluation ◽  
Detection And Identification ◽  
Cross Correlation Analysis ◽  
Observer Model ◽  
The Ideal

Many of the metrics developed for informational imaging are useful in automotive imaging, since many of the tasks – for example, object detection and identification – are similar. This work discusses sensor characterization parameters for the Ideal Observer SNR model, and elaborates on the noise power spectrum. It presents cross-correlation analysis results for matched-filter detection of a tribar pattern in sets of resolution target images that were captured with three image sensors over a range of illumination levels. Lastly, the work compares the crosscorrelation data to predictions made by the Ideal Observer Model and demonstrates good agreement between the two methods on relative evaluation of detection capabilities.

The interpretation of singular nouns in the scope of an event-distributive quantifier

2019 ◽  
Vol 5 (1) ◽  
pp. 1-9
Author(s):  
Piotr Gulgowski
Keyword(s):  
Present Experiment ◽  
Multiple Objects ◽  
Multiple Events ◽  
Singular Noun ◽  
Distributive Operator

Abstract Singular nouns in the scope of a distributive operator have been shown to be treated as conceptually plural (Patson and Warren, 2010). The source of this conceptual plurality is not fully clear. In particular, it is not known whether the concept of plurality associated with a singular noun originates from distributing over multiple objects or multiple events. In the present experiment, iterative expressions (distribution over events) were contrasted with collective and distributive sentences using a Stroop-like interference technique (Berent, Pinker, Tzelgov, Bibi, and Goldfarb, 2005; Patson and Warren, 2010). A trend in the data suggests that event distributivity does not elicit a plural interpretation of a grammatically singular noun, however the results were not statistically significant. Possible causes of the non-significant results are discussed.

Assimilation of various organic carbon sources by Haematococcus strains

2009 ◽  
Vol 57 (2) ◽  
pp. 231-237
Author(s):  
M. Zych ◽  
A. Stolarczyk ◽  
K. Maca ◽  
A. Banaś ◽  
K. Termińska-Pabis ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Organic Compounds ◽  
Present Experiment ◽  
Carbon Sources ◽  
Growth Conditions ◽  
Mixotrophic Growth ◽  
Naturally Occurring ◽  
Organic Carbon Sources ◽  
Secondary Carotenoids ◽  
Colour Changes

Differences in the assimilation of individual organic compounds (5 mM sugars and L-asparagine) under mixotrophic growth conditions were described for three naturally occurring Haematococcus strains.The effects of assimilation were measured by the growth intensity and size of algal cells, and the effect of colour changes in the cultures was observed. Some compounds caused the cell colouration to change from green to yellow, being the result of chlorophyll disappearance and the accumulation of yellow secondary carotenoids. In the present experiment none of the cultures turned red, thus excluding the intense accumulation of the commercially interesting carotenoid, astaxanthin.

Delay of Reinforcement Effects: Timing of Reinforcement or Narrow Goal-Box Confinement

2000 ◽  
Vol 87 (3) ◽  
pp. 988-990 ◽  
Author(s):  
Richard S. Calef ◽  
Michael C. Choban ◽  
Katherine R. Glenney ◽  
Ruth A. Calef ◽  
Julie N. Godbey ◽  
...  
Keyword(s):  
Present Experiment ◽  
Delay Of Reinforcement

The present experiment investigated whether narrow goal-box confinement in studies of delay of reinforcement in the runway may have had aversive or punishing effects. Analysis showed no difference in performance between groups of rats who were either confined in a narrow goal-box or a large compartment while receiving their delay of reinforcement. The results suggest that narrow goal-box confinement does not have aversive characteristics.

Strawberry phenolic extracts effectively mitigated metabolic disturbances associated with high-fat ingestion in rats depending on the ellagitannin polymerization degree

2021 ◽  
Author(s):  
Ewa Żary-Sikorska ◽  
Bartosz Fotschki ◽  
Krzysztof Kołodziejczyk ◽  
Adam Jurgoński ◽  
Monika Kosmala ◽  
...  
Keyword(s):  
Present Experiment ◽  
Negative Consequences ◽  
Polymerization Degree ◽  
High Fat ◽  
Metabolic Disturbances ◽  
Phenolic Extracts

In the present experiment it was hypothesised that dietary strawberry ellagitannin-rich extracts would mitigate negative consequences associated with consumption.

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