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A Three-Feature Model to Predict Colour Change Blindness
[article]
2019
arXiv
pre-print
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We introduce a fully automated model to predict colour change blindness in cartoon images based on two low-level image features and observer experience. ...
Change blindness is a striking shortcoming of our visual system which is exploited in the popular "Spot the difference" game. ...
PREDICTION OF CHANGE BLINDNESS A. ...
arXiv:1909.04147v1
fatcat:mq4z2ksmfbcpnbkk326wtzojtu
A Three-Feature Model to Predict Colour Change Blindness
2019
Vision
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In this paper, we introduce a fully automated model to predict colour change blindness in cartoon images based on image complexity, change magnitude and observer experience. ...
Change blindness is a striking shortcoming of our visual system which is exploited in the popular 'Spot the difference' game, as it makes us unable to notice large visual changes happening right before ...
Acknowledgments: The authors would like to thank Li-Qian Ma for providing the implementation of their change blindness model.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/vision3040061
pmid:31735862
pmcid:PMC6969898
fatcat:jlizgkc2jzaoznjnlg4wx35ezm
Distractor-induced blindness for orientation changes and coherent motion
2011
Vision Research
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In a series of three experiments we show that distractors have to share the feature characteristics of the target in order to reduce its detectability. ...
For this reason, targets were either defined by motion coherence ("motion blindness") or orientation changes ("orientation blindness"). ...
The results of Experiment 3 are not in line with the predictions of a pure top-down model. ...
doi:10.1016/j.visres.2011.06.007
pmid:21703293
fatcat:p4hdpfajg5hnbivqscfmdclsxm
Flexible Resource Allocation for the Detection of Changing Visual Features
2011
Perception
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objects, and that this level of detectability could be predicted by a simple model of probability summation. ...
We suggest they are adequately explained by a flexible-resourceallocation model rather than a slot-allocation model. ...
Experiment 1 is designed primarily to establish a magnitude of change for the three change types (colour, speed, and size) that is equivalent. ...
doi:10.1068/p6892
pmid:21692421
fatcat:c6qafctmhbhhxnl6lyobk4jh6m
Limited memory for ensemble statistics in visual change detection
2021
Cognition
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optimal summation model, which was blind to the ensemble mean, in five out of six experiments. ...
We made specific predictions of observers' sensitivity using an optimal summation model that integrates evidence across separate items but does not detect changes in ensemble statistics. ...
The optimal summation model, blind to ensemble statistics, therefore accurately predicted performance in the mean-change condition, with a meta-analytic Bayes factor of 8.07, constituting moderate evidence ...
doi:10.1016/j.cognition.2021.104763
pmid:34062339
pmcid:PMC7614705
fatcat:jx2ofqnmizdn5iwhjqlsccyone
Blind Quality Metric via Measurement of Contrast, Texture, and Colour in Night-Time Scenario
2021
KSII Transactions on Internet and Information Systems
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Finally, the quality prediction model is conducted by the support vector regression (SVR) based on extracted contrast, texture, and colour features. ...
A new blind quality assessment metric is presented for realistic night-time scenario through a comprehensive consideration of contrast, texture, and colour in this article. ...
After feature extraction, SVR is adopted to train the quality prediction model. ...
doi:10.3837/tiis.2021.11.010
fatcat:q3i5fxu4m5cyfh227t5whtee3a
A semi-automated approach to balancing of bottom-up salience for predicting change detection performance
2010
Journal of Vision
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Previous change blindness studies have failed to address the importance of balancing low-level visual salience when producing experimental stimuli for a change detection task. ...
When the saliency of the changes are similar, addition/removal changes are detected more readily than colour changes to the scene. ...
Many thanks also to Dan Simons for helpful discussions. ...
doi:10.1167/10.6.3
pmid:20884552
fatcat:u6nxw3eqorcpfa3privjttnqbm
Feature blindness: a challenge for understanding and modelling visual object recognition
[article]
2021
bioRxiv
pre-print
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Instead, they learned to rely on global features such as colour or shape, even when these features were not the most predictive. ...
When these features were absent they failed to learn the task entirely. By contrast, ideal inference models as well as CNNs always learned to categorise objects based on the most predictive feature. ...
These results show that humans are blind to a wide range of non-shape predictive features when classifying objects, and if models are going to be used as theories of human vision, they should be blind ...
doi:10.1101/2021.10.20.465074
fatcat:vfnp3x5xqza2lk37by53nxm2ra
Iridescent colour production in hairs of blind golden moles (Chrysochloridae)
2012
Biology Letters
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Doucet for the use of microspectrophotometer, Museum of Vertebrate Zoology for specimen use, and Tim Caro and three anonymous reviewers for their helpful comments and suggestions. ...
We compared measured and predicted reflectance curves to determine the accuracy of modelling. ...
Changes in the numbers and/or thickness of layers can result in remarkable variation in local reflectance and consequently to the perceived colour [1] . ...
doi:10.1098/rsbl.2011.1168
pmid:22279154
pmcid:PMC3367760
fatcat:ot2bfyrnnvca3oplcivf2sseyi
Comparative Study of Diabetic Retinopathy Detection Using Machine Learning Techniques
2022
International Journal for Research in Applied Science and Engineering Technology
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Exudates, haemorrhages, and micro aneurysms are three features that this study suggests extracting using machine learning. ...
Abstract: Untreated diabetic retinopathy, a condition brought on by unmanaged chronic diabetes, can result in total blindness. ...
The images in the dataset were captured using a variety of camera models and types, which can change how the left and right sides seem to the eye. ...
doi:10.22214/ijraset.2022.46101
fatcat:top5ltt7kfcg3gyydvnv6xeusq
Evidence of change blindness in subjective image fidelity assessment
2017
2017 IEEE International Conference on Image Processing (ICIP)
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Change blindness is a striking phenomenon which basically means that we can look without seeing. ...
Furthermore, a comparison of the efficiency of six state-of-the-art image fidelity assessment models (so-called metrics) reveals that five of them perform significantly better at predicting results obtained ...
The models are the Multi-Scale Colour Image Difference (MS-iCID) [17] , the Visual Saliency Index (VSI) [10] , the Feature Similarity Index with colour component (FSIMc) [19] , the PSNR-HA [20] , Multi-Scale ...
doi:10.1109/icip.2017.8296864
dblp:conf/icip/MoanP17
fatcat:czuryzteqvhgjm646ymr57yjoy
Sexing starlingsSturnus vulgarisusing iris colour
2005
Ringing & Migration
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We took blood samples from 100 post-fledging juvenile Starlings Sturnus vulgaris for DNA sexing in late August, and scored the traits that are commonly thought to predict sex in adults: iris colour, length ...
These features were still reliable in the following February, when the birds had come into breeding plumage. At this stage, the colour of the base of the bill was 100% accurate in predicting sex. ...
This study was funded by Universities Federation of Animal Welfare studentship to ELS. ...
doi:10.1080/03078698.2005.9674332
fatcat:zent2ovuhbggvkx7nkyfagrsny
The Best of Both Worlds: a Framework for Combining Degradation Prediction with High Performance Super-Resolution Networks
[article]
2022
arXiv
pre-print
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In this work, we present a framework for combining any blind SR prediction mechanism with any deep SR network, using a metadata insertion block to insert prediction vectors into SR network feature maps ...
or B) attempt to predict the degradations an LR image has suffered and use these to inform a customised SR network. ...
By using a single metadata insertion block to influence the feature maps of a convolutional layer, any degradation vector from a prediction model can, in many cases, be used to improve SR network performance ...
arXiv:2211.05018v1
fatcat:w6tb5k6gobgo7erbwpjisubj64
Visualization of quality of 3D tomographic images in construction of digital rock model
Визуализация качества трехмерных томографических изображений при создании цифровой модели керна
2020
Scientific Visualization
Визуализация качества трехмерных томографических изображений при создании цифровой модели керна
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The choice of colour scale is considered to facilitate the analysis of graphical information for people with colour vision deficiency. ...
Using X-ray or FIB-SEM tomography, a 3D model of a core sample is constructed for mathematical simulations of fluid flow in porous media and evaluation of physical characteristics of rock. ...
Distortion of natural images are assumed to change the orientations of local gradients in a predictable way. ...
doi:10.26583/sv.12.1.06
fatcat:wl3gedk7njewppy3ou4yjbhrn4
Artificial Intelligence and Earth Observation to Explore Water Quality in the Wadden Sea
[chapter]
2018
Earth Observation Open Science and Innovation
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An artificial-intelligence technique, inductive learning, is used to analyze the data and provide predictions in terms of water colour represented via the Forel-Ule scale (a comparative scale for colour ...
This chapter describes a decision support system used to predict optical water-quality indicators in the Wadden Sea, which is an intertidal marine system, where natural processes related to sediment transport ...
Each leaf node in a tree specifies the value to be returned. The aim here is to learn a model for the target label FU-Colour. ...
doi:10.1007/978-3-319-65633-5_18
fatcat:e46zyapdmvcgrdre6tona6wdfa
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