{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T01:36:47Z","timestamp":1774489007095,"version":"3.50.1"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"21","license":[{"start":{"date-parts":[[2024,8,10]],"date-time":"2024-08-10T00:00:00Z","timestamp":1723248000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,8,10]],"date-time":"2024-08-10T00:00:00Z","timestamp":1723248000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100013357","name":"Indian Statistical Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013357","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s10489-024-05658-w","type":"journal-article","created":{"date-parts":[[2024,8,10]],"date-time":"2024-08-10T07:02:32Z","timestamp":1723273352000},"page":"10259-10283","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Deep learning models for perception of brightness related illusions"],"prefix":"10.1007","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5601-591X","authenticated-orcid":false,"given":"Amrita","family":"Mukherjee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Avijit","family":"Paul","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kuntal","family":"Ghosh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,10]]},"reference":[{"issue":"5","key":"5658_CR1","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1016\/S1364-6613(97)01060-7","volume":"1","author":"RL Gregory","year":"1997","unstructured":"Gregory RL (1997) Visual illusions classified. Trends Cognit Sci 1(5):190\u2013194. https:\/\/doi.org\/10.1016\/S1364-6613(97)01060-7","journal-title":"Visual illusions classified. Trends Cognit Sci"},{"key":"5658_CR2","volume-title":"Incognito","author":"D Eagleman","year":"2011","unstructured":"Eagleman D (2011) Incognito, Enhanced. The Secret Lives of The Brain, Knopf, London","edition":"Enhanced"},{"key":"5658_CR3","volume-title":"The Oxford Compendium of Visual Illusions","author":"AG Shapiro","year":"2016","unstructured":"Shapiro AG, Todorovic D (2016) The Oxford Compendium of Visual Illusions. Oxford University Press, London"},{"issue":"3","key":"5658_CR4","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1068\/p040349","volume":"4","author":"JP Frisby","year":"1975","unstructured":"Frisby JP, Clatworthy JL (1975) Illusory contours: Curious cases of simultaneous brightness contrast? Percept 4(3):349\u2013357. https:\/\/doi.org\/10.1068\/p040349","journal-title":"Percept"},{"issue":"4","key":"5658_CR5","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1068\/p080413","volume":"8","author":"M White","year":"1979","unstructured":"White M (1979) A new effect of pattern on perceived lightness. Percept 8(4):413\u2013416. https:\/\/doi.org\/10.1068\/p080413","journal-title":"Percept"},{"issue":"21","key":"5658_CR6","doi-asserted-by":"publisher","first-page":"2483","DOI":"10.1016\/j.visres.2004.05.015","volume":"44","author":"B Blakeslee","year":"2004","unstructured":"Blakeslee B, McCourt ME (2004) A unified theory of brightness contrast and assimilation incorporating oriented multiscale spatial filtering and contrast normalization. Vision Res 44(21):2483\u20132503. https:\/\/doi.org\/10.1016\/j.visres.2004.05.015","journal-title":"Vision Res"},{"key":"5658_CR7","doi-asserted-by":"publisher","unstructured":"Watanabe E, Kitaoka A, Sakamoto K, Yasugi M, Tanaka K (2018) Illusory motion reproduced by deep neural networks trained for prediction. Frontiers Psychol 345. https:\/\/doi.org\/10.3389\/fpsyg.2018.00345","DOI":"10.3389\/fpsyg.2018.00345"},{"key":"5658_CR8","doi-asserted-by":"publisher","unstructured":"Gomez-Villa A, Martin A, Vazquez-Corral J, Bertalmio M (2019) Convolutional neural networks can be deceived by visual illusions. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. pp 12309\u201312317. https:\/\/doi.org\/10.48550\/arXiv.1811.10565","DOI":"10.48550\/arXiv.1811.10565"},{"key":"5658_CR9","unstructured":"Alain G, Bengio Y (2014) What regularized auto-encoders learn from the data-generating distribution. The J Mach Learn Res 15(1), 3563\u20133593. https:\/\/doi.org\/10.48550\/arXiv.1211.4246"},{"key":"5658_CR10","doi-asserted-by":"publisher","unstructured":"Yampolskiy O, Fischer P, Brox T (2015) U-net: Convolutional networks for biomedical image segmentation. In: International conference on medical image computing and computer-assisted intervention. pp 234\u2013241, Springer. https:\/\/doi.org\/10.48550\/arXiv.2105.13067","DOI":"10.48550\/arXiv.2105.13067"},{"key":"5658_CR11","doi-asserted-by":"publisher","unstructured":"Zhou Z, Rahman TN, S.\u00a0Md\u00a0Mahfuzur JL (2018) Unet++: A nested u-net architecture for medical image segmentation. In: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support. pp 3\u201311. Springer, New York. https:\/\/doi.org\/10.48550\/arXiv.1807.10165","DOI":"10.48550\/arXiv.1807.10165"},{"issue":"8","key":"5658_CR12","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1021\/ac60214a047","volume":"36","author":"A Savitzky","year":"1964","unstructured":"Savitzky A, Golay MJ (1964) Smoothing and differentiation of data by simplified least squares procedures. Anal Chem 36(8):1627\u20131639. https:\/\/doi.org\/10.1021\/ac60214a047","journal-title":"Anal Chem"},{"issue":"4","key":"5658_CR13","doi-asserted-by":"publisher","first-page":"1218","DOI":"10.1109\/TSA.2005.860851","volume":"14","author":"J Chen","year":"2006","unstructured":"Chen J, Benesty J, Huang Y, Doclo S (2006) New insights into the noise reduction Wiener filter. IEEE Transactions on audio, speech, and language processing 14(4):1218\u20131234. https:\/\/doi.org\/10.1109\/TSA.2005.860851","journal-title":"IEEE Transactions on audio, speech, and language processing"},{"key":"5658_CR14","doi-asserted-by":"crossref","unstructured":"Dabov K, Foi AVK, Egiazarian K (2007) Joint image sharpening and denoising by 3d transform-domain collaborative filtering. In: Proc. 2007 Int. TICSP workshop spectral meth. multirate signal process., SMMSP, vol. 2007. Citeseer","DOI":"10.1109\/TIP.2007.901238"},{"key":"5658_CR15","doi-asserted-by":"publisher","unstructured":"Buades A, Coll B, Morel JM (2005) A non-local algorithm for image denoising. In: 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR\u201905), vol. 2. pp 60\u201365, IEEE. https:\/\/doi.org\/10.1109\/CVPR.2005.38","DOI":"10.1109\/CVPR.2005.38"},{"key":"5658_CR16","doi-asserted-by":"publisher","first-page":"554","DOI":"10.3389\/fnins.2021.629469","volume":"15","author":"RG Alexander","year":"2021","unstructured":"Alexander RG, Yazdanie F, Waite S, Chaudhry ZA, Kolla S, Macknik SL, Martinez-Conde S (2021) Visual Illusions in Radiology: untrue perceptions in medical images and their implications for diagnostic accuracy. Frontiers Neurosci 15:554. https:\/\/doi.org\/10.3389\/fnins.2021.629469","journal-title":"Frontiers Neurosci"},{"issue":"6","key":"5658_CR17","doi-asserted-by":"publisher","first-page":"928","DOI":"10.1513\/AnnalsATS.201412-576AS","volume":"12","author":"MO Kattea","year":"2015","unstructured":"Kattea MO, Lababede O (2015) Differentiating pneumothorax from the common radiographic skinfold artifact. Annals American Thoracic Soc 12(6):928\u2013931. https:\/\/doi.org\/10.1513\/AnnalsATS.201412-576AS","journal-title":"Annals American Thoracic Soc"},{"issue":"7","key":"5658_CR18","doi-asserted-by":"publisher","first-page":"2087","DOI":"10.1148\/rg.337125204","volume":"33","author":"CE Buckle","year":"2013","unstructured":"Buckle CE, Udawatta V, Straus CM (2013) Now you see it, now you don\u2019t: visual illusions in radiology. Radiograph 33(7):2087\u20132102. https:\/\/doi.org\/10.1148\/rg.337125204","journal-title":"Radiograph"},{"issue":"10","key":"5658_CR19","doi-asserted-by":"publisher","first-page":"1675","DOI":"10.1037\/xge0000553","volume":"148","author":"E Picon","year":"2019","unstructured":"Picon E, Dramkin D, Odic D (2019) Visual illusions help reveal the primitives of number perception. JExp Psychol: Gen 148(10):1675. https:\/\/doi.org\/10.1037\/xge0000553","journal-title":"JExp Psychol: Gen"},{"key":"5658_CR20","volume-title":"The Nature of Psychology","author":"KJW Craik","year":"1966","unstructured":"Craik KJW (1966) The Nature of Psychology. Cambridge University Press, London"},{"issue":"3","key":"5658_CR21","doi-asserted-by":"publisher","first-page":"241","DOI":"10.3758\/BF03207869","volume":"43","author":"S Grossberg","year":"1988","unstructured":"Grossberg S, Todorovic D (1988) Neural dynamics of 1-d and 2-d brightness perception: A unified model of classical and recent phenomena. Percept Psychophys 43(3):241\u2013277. https:\/\/doi.org\/10.3758\/BF03207869","journal-title":"Percept Psychophys"},{"key":"5658_CR22","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/9780262514620.001.0001","volume-title":"Vision: a computational investigation into the human representation and processing of visual information","author":"D Marr","year":"2010","unstructured":"Marr D (2010) Vision: a computational investigation into the human representation and processing of visual information. MIT press, Boston"},{"issue":"20","key":"5658_CR23","doi-asserted-by":"publisher","first-page":"2849","DOI":"10.1016\/S0042-6989(97)00086-2","volume":"37","author":"B Blakeslee","year":"1997","unstructured":"Blakeslee B, McCourt ME (1997) Similar mechanisms underlie simultaneous brightness contrast and grating induction. Vision Res 37(20):2849\u20132869. https:\/\/doi.org\/10.1016\/S0042-6989(97)00086-2","journal-title":"Vision Res"},{"issue":"1","key":"5658_CR24","doi-asserted-by":"publisher","first-page":"306","DOI":"10.3758\/s13428-015-0573-4","volume":"48","author":"B Blakeslee","year":"2016","unstructured":"Blakeslee B, Cope D, McCourt ME (2016) The Oriented Difference of Gaussians (ODOG) model of brightness perception: Overview and executable Mathematica notebooks. Behavior Res Methods 48(1):306\u2013312. https:\/\/doi.org\/10.3758\/s13428-015-0573-4","journal-title":"Behavior Res Methods"},{"issue":"12","key":"5658_CR25","doi-asserted-by":"publisher","first-page":"1631","DOI":"10.1016\/j.visres.2007.02.017","volume":"47","author":"AE Robinson","year":"2007","unstructured":"Robinson AE, Hammon PS, de Sa VR (2007) Explaining brightness illusions using spatial filtering and local response normalization. Vision Res 47(12):1631\u20131644. https:\/\/doi.org\/10.1016\/j.visres.2007.02.017","journal-title":"Vision Res"},{"issue":"2","key":"5658_CR26","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1007\/s00422-005-0038-4","volume":"94","author":"K Ghosh","year":"2006","unstructured":"Ghosh K, Sarkar S, Bhaumik K (2006) A possible explanation of the low-level brightness-contrast illusions in the light of an extended classical receptive field model of retinal ganglion cells. Biol Cybernet 94(2):89\u201396. https:\/\/doi.org\/10.1007\/s00422-005-0038-4","journal-title":"Biol Cybernet"},{"key":"5658_CR27","doi-asserted-by":"publisher","unstructured":"Qin Z, Yu FCL, Chen X (2018) How convolutional neural network see the world- A survey of convolutional neural network visualization methods. arXiv:1804.11191, https:\/\/doi.org\/10.3934\/MFC.2018008","DOI":"10.3934\/MFC.2018008"},{"issue":"10","key":"5658_CR28","doi-asserted-by":"publisher","first-page":"1995","DOI":"10.5555\/303568.303704","volume":"3361","author":"Y LeCun","year":"1995","unstructured":"LeCun Y, Bengio Y et al (1995) Convolutional networks for images, speech, and time series. The Handbook of Brain Theory Neural Netw 3361(10):1995. https:\/\/doi.org\/10.5555\/303568.303704","journal-title":"The Handbook of Brain Theory Neural Netw"},{"key":"5658_CR29","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1145\/3458709.3458952","volume":"2021","author":"Y Kubota","year":"2021","unstructured":"Kubota Y, Hiyama A, Inami M (2021) A machine learning model perceiving brightness optical illusions: Quantitative evaluation with psychophysical data. Proc Augmented Humans Inter Conf 2021:174\u2013182. https:\/\/doi.org\/10.1145\/3458709.3458952","journal-title":"Proc Augmented Humans Inter Conf"},{"key":"5658_CR30","doi-asserted-by":"publisher","unstructured":"Gomez-Villa A, Martin A, Vazquez-Corral J, Malo J, Bertalmio M (2019) Synthesizing visual illusions using generative adversarial networks. arXiv:1911.09599, https:\/\/doi.org\/10.48550\/arXiv.1911.09599","DOI":"10.48550\/arXiv.1911.09599"},{"issue":"7","key":"5658_CR31","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1016\/j.visres.2010.09.012","volume":"51","author":"FA Kingdom","year":"2011","unstructured":"Kingdom FA (2011) Lightness, brightness and transparency: A quarter century of new ideas, captivating demonstrations and unrelenting controversy. Vision Res 51(7):652\u2013673. https:\/\/doi.org\/10.1016\/j.visres.2010.09.012","journal-title":"Vision Res"},{"key":"5658_CR32","doi-asserted-by":"publisher","unstructured":"Serre T, Wolf L, Poggio T (2005) Object recognition with features inspired by visual cortex. In: 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR\u201905), vol. 2. pp 994\u20131000. https:\/\/doi.org\/10.1109\/CVPR.2005.254. Ieee","DOI":"10.1109\/CVPR.2005.254"},{"key":"5658_CR33","doi-asserted-by":"publisher","first-page":"112","DOI":"10.3389\/fncom.2014.00112","volume":"8","author":"A Zeman","year":"2014","unstructured":"Zeman A, Obst O, Brooks KR (2014) Complex cells decrease errors for the m\u00fcller-lyer illusion in a model of the visual ventral stream. Frontiers Comput Neurosci 8:112. https:\/\/doi.org\/10.3389\/fncom.2014.00112","journal-title":"Frontiers Comput Neurosci"},{"issue":"23","key":"5658_CR34","doi-asserted-by":"publisher","first-page":"2381","DOI":"10.1016\/j.visres.2010.09.021","volume":"50","author":"E Watanabe","year":"2010","unstructured":"Watanabe E, Matsunaga W, Kitaoka A (2010) Motion signals deflect relative positions of moving objects. Vision Res 50(23):2381\u20132390. https:\/\/doi.org\/10.1016\/j.visres.2010.09.021","journal-title":"Vision Res"},{"issue":"4","key":"5658_CR35","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1159\/000437271","volume":"48","author":"MM Nour","year":"2015","unstructured":"Nour MM, Nour JM (2015) Perception, illusions and bayesian inference. Psychopathol 48(4):217\u2013221. https:\/\/doi.org\/10.1159\/000437271","journal-title":"Psychopathol"},{"issue":"3","key":"5658_CR36","doi-asserted-by":"publisher","first-page":"0151194","DOI":"10.1371\/journal.pone.0151194","volume":"11","author":"R Raman","year":"2016","unstructured":"Raman R, Sarkar S (2016) Predictive coding: a possible explanation of filling-in at the blind spot. PloS one 11(3):0151194. https:\/\/doi.org\/10.1371\/journal.pone.0151194","journal-title":"PloS one"},{"key":"5658_CR37","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1146\/annurev-vision-082114-035447","volume":"1","author":"N Kriegeskorte","year":"2015","unstructured":"Kriegeskorte N (2015) Deep neural networks: a new framework for modeling biological vision and brain information processing. Annual Review Vision Sci 1:417\u2013446. https:\/\/doi.org\/10.1146\/annurev-vision-082114-035447","journal-title":"Annual Review Vision Sci"},{"issue":"9","key":"5658_CR38","doi-asserted-by":"publisher","first-page":"1127","DOI":"10.1038\/s41562-021-01194-6","volume":"5","author":"B Peters","year":"2021","unstructured":"Peters B, Kriegeskorte N (2021) Capturing the objects of vision with neural networks. Nat Human Behaviour 5(9):1127\u20131144. https:\/\/doi.org\/10.1038\/s41562-021-01194-6","journal-title":"Nat Human Behaviour"},{"key":"5658_CR39","doi-asserted-by":"publisher","unstructured":"Kietzmann TC, McClure P, Kriegeskorte N (2017) Deep neural networks in computational neuroscience. BioRxiv. 133504. https:\/\/doi.org\/10.1093\/acrefore\/9780190264086.013.46","DOI":"10.1093\/acrefore\/9780190264086.013.46"},{"key":"5658_CR40","doi-asserted-by":"publisher","unstructured":"Bowers JS, Malhotra G, Dujmovi\u0107 M, Montero ML, Tsvetkov C, Biscione V, Puebla G, Adolfi F, Hummel JE, Heaton RF et al. (2023) Deep problems with neural network models of human vision. Behavioral Brain Sci 46:385. https:\/\/doi.org\/10.31234\/osf.io\/5zf4s","DOI":"10.31234\/osf.io\/5zf4s"},{"key":"5658_CR41","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1017\/S0140525X23001759","volume":"46","author":"KS Chandran","year":"2023","unstructured":"Chandran KS, Paul AM, Paul A, Ghosh K (2023) Psychophysics may be the game-changer for deep neural networks (dnns) to imitate the human vision. Behavioral Brain Sci 46:388. https:\/\/doi.org\/10.1017\/S0140525X23001759","journal-title":"Behavioral Brain Sci"},{"key":"5658_CR42","volume-title":"Vision Science: Photons to Phenomenology","author":"SE Palmer","year":"1999","unstructured":"Palmer SE (1999) Vision Science: Photons to Phenomenology. MIT press, Boston"},{"key":"5658_CR43","doi-asserted-by":"publisher","unstructured":"Ratliff F (1965) Mach bands: quantitative studies on neural networks. Retina. San Francisco, CA: Holden-Day. https:\/\/doi.org\/10.1126\/science.150.3696.596","DOI":"10.1126\/science.150.3696.596"},{"issue":"2","key":"5658_CR44","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1152\/jn.00635.2016","volume":"117","author":"JE Niemeyer","year":"2017","unstructured":"Niemeyer JE, Paradiso MA (2017) Contrast sensitivity, V1 neural activity, and natural vision. J Neurophysiol 117(2):492\u2013508. https:\/\/doi.org\/10.1152\/jn.00635.2016","journal-title":"J Neurophysiol"},{"issue":"26","key":"5658_CR45","doi-asserted-by":"publisher","first-page":"4361","DOI":"10.1016\/S0042-6989(99)00119-4","volume":"39","author":"B Blakeslee","year":"1999","unstructured":"Blakeslee B, McCourt ME (1999) A multiscale spatial filtering account of the white effect, simultaneous brightness contrast and grating induction. Vision Res 39(26):4361\u20134377. https:\/\/doi.org\/10.1016\/S0042-6989(99)00119-4","journal-title":"Vision Res"},{"issue":"23","key":"5658_CR46","doi-asserted-by":"publisher","first-page":"2659","DOI":"10.1016\/j.visres.2004.06.005","volume":"44","author":"W McIlhagga","year":"2004","unstructured":"McIlhagga W (2004) Denoising and contrast constancy. Vision Res 44(23):2659\u20132666. https:\/\/doi.org\/10.1016\/j.visres.2004.06.005","journal-title":"Vision Res"},{"issue":"6232","key":"5658_CR47","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1038\/340385a0","volume":"340","author":"M Morgan","year":"1989","unstructured":"Morgan M, Benton S (1989) Motion-deblurring in human vision. Nat 340(6232):385\u2013386. https:\/\/doi.org\/10.1038\/340385a0","journal-title":"Motion-deblurring in human vision. Nat"},{"key":"5658_CR48","doi-asserted-by":"publisher","unstructured":"Barbu T (2013) Variational image denoising approach with diffusion porous media flow. In: Abstract and applied analysis, vol. 2013. Hindawi, https:\/\/doi.org\/10.1155\/2013\/856876","DOI":"10.1155\/2013\/856876"},{"key":"5658_CR49","unstructured":"Gedraite ES, Hadad M (2011) Investigation on the effect of a gaussian blur in image filtering and segmentation. In: Proceedings ELMAR-2011. pp 393\u2013396, IEEE"},{"issue":"5","key":"5658_CR50","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1016\/j.camwa.2015.05.026","volume":"70","author":"F Dong","year":"2015","unstructured":"Dong F, Chen Y, Kong D-X, Yang B (2015) Salt and pepper noise removal based on an approximation of l0 norm. Comput Math Appl 70(5):789\u2013804. https:\/\/doi.org\/10.1016\/j.camwa.2015.05.026","journal-title":"Comput Math Appl"},{"issue":"1","key":"5658_CR51","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.ijleo.2004.12.004","volume":"116","author":"J Garcia-Sucerquia","year":"2005","unstructured":"Garcia-Sucerquia J, Ram\u00edrez JAH, Prieto DV (2005) Reduction of speckle noise in digital holography by using digital image processing. Optik 116(1):44\u201348. https:\/\/doi.org\/10.1016\/j.ijleo.2004.12.004","journal-title":"Optik"},{"issue":"3","key":"5658_CR52","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1007\/s10851-007-0652-y","volume":"27","author":"T Le","year":"2007","unstructured":"Le T, Chartrand R, Asaki TJ (2007) A variational approach to reconstructing images corrupted by poisson noise. J Math Imaging Vision 27(3):257\u2013263. https:\/\/doi.org\/10.1007\/s10851-007-0652-y","journal-title":"J Math Imaging Vision"},{"key":"5658_CR53","doi-asserted-by":"publisher","unstructured":"Cho S, Matsushita Y, Lee S (2007) Removing non-uniform motion blur from images. In: 2007 IEEE 11th International conference on computer vision. pp 1\u20138, IEEE. https:\/\/doi.org\/10.1109\/ICCV.2007.4408904","DOI":"10.1109\/ICCV.2007.4408904"},{"key":"5658_CR54","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1007\/978-1-4842-2766-4_7","volume-title":"Deep Learning with Python","author":"N Ketkar","year":"2017","unstructured":"Ketkar N (2017) Introduction to keras. Deep Learning with Python. Springer, New York, pp 97\u2013111"},{"issue":"6","key":"5658_CR55","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1167\/8.6.288","volume":"8","author":"A Shapiro","year":"2008","unstructured":"Shapiro A, Knight E, Lu Z-L (2008) Spatial scale models of lightness illusions: contrast, anchoring, and tunable filters. J Vision 8(6):288\u2013288. https:\/\/doi.org\/10.1167\/8.6.288","journal-title":"J Vision"},{"issue":"2","key":"5658_CR56","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/0042-6989(78)90189-x","volume":"18","author":"SM Anstis","year":"1978","unstructured":"Anstis SM, Howard IP, Rogers B (1978) A Craik-O\u2019Brien-Cornsweet illusion for visual depth. Vision Res 18(2):213\u2013217. https:\/\/doi.org\/10.1016\/0042-6989(78)90189-x","journal-title":"Vision Res"},{"key":"5658_CR57","unstructured":"Adelson EH, Edward H (2000) 24 Lightness Perception and Lightness Illusions. The New Cognit Neurosci 339"},{"issue":"3","key":"5658_CR58","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1511\/2002.9.236","volume":"90","author":"D Purves","year":"2002","unstructured":"Purves D, Lotto RB, Nundy S (2002) Why we see what we do: A probabilistic strategy based on past experience explains the remarkable difference between what we see and physical reality. American Sci 90(3):236\u2013243","journal-title":"American Sci"},{"key":"5658_CR59","doi-asserted-by":"publisher","unstructured":"Laeng B, Faerevaag FS, Tanggaard S, von Tetzchner S (2018) Pupillary responses to illusions of brightness in autism spectrum disorder. i-Perception 9(3):2041669518771716. https:\/\/doi.org\/10.1177\/2041669518771716","DOI":"10.1177\/2041669518771716"},{"issue":"9","key":"5658_CR60","doi-asserted-by":"publisher","first-page":"1031","DOI":"10.1068\/p3109","volume":"30","author":"P Bressan","year":"2001","unstructured":"Bressan P (2001) Explaining lightness illusions. Percept 30(9):1031\u20131046. https:\/\/doi.org\/10.1068\/p3109","journal-title":"Explaining lightness illusions. Percept"},{"issue":"6","key":"5658_CR61","doi-asserted-by":"publisher","first-page":"1346","DOI":"10.1152\/jn.00127.2013","volume":"110","author":"MS Pratte","year":"2013","unstructured":"Pratte MS, Ling S, Swisher JD, Tong F (2013) How attention extracts objects from noise. J Neurophysiol 110(6):1346\u20131356. https:\/\/doi.org\/10.1152\/jn.00127.2013","journal-title":"J Neurophysiol"},{"issue":"3","key":"5658_CR62","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1113\/jphysiol.1975.sp011162","volume":"252","author":"M Georgeson","year":"1975","unstructured":"Georgeson M, Sullivan G (1975) Contrast constancy: deblurring in human vision by spatial frequency channels. The J Physiol 252(3):627\u2013656. https:\/\/doi.org\/10.1113\/jphysiol.1975.sp011162","journal-title":"The J Physiol"},{"key":"5658_CR63","doi-asserted-by":"publisher","unstructured":"Mazade R, Jin J, Rahimi-Nasrabadi H, Najafian S, Pons C, Alonso J-M (2022) Cortical mechanisms of visual brightness. Cell Reports 40(13). https:\/\/doi.org\/10.1016\/j.celrep.2022.111438","DOI":"10.1016\/j.celrep.2022.111438"},{"key":"5658_CR64","doi-asserted-by":"publisher","unstructured":"Rekauzke S, Nortmann N, Staadt R, Hock HS, Sch\u00f6ner G, Jancke D (2016) Temporal asymmetry in dark-bright processing initiates propagating activity across primary visual cortex. J Neurosci 36(6):1902\u20131913. https:\/\/doi.org\/10.1523\/JNEUROSCI.3235-15.2016","DOI":"10.1523\/JNEUROSCI.3235-15.2016"},{"key":"5658_CR65","doi-asserted-by":"publisher","unstructured":"Geier J, Bernath L, Hudak M, Sera L (2008) Straightness as the main factor of the Hermann grid illusion. Percept 37(5):651\u2013665. https:\/\/doi.org\/10.1068\/p5622","DOI":"10.1068\/p5622"},{"key":"5658_CR66","unstructured":"CHRISTIAN B, (2022) The alignment problem: machine learning and human values. WW Norton & Company, New York"},{"issue":"3","key":"5658_CR67","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1007\/s11023-020-09539-2FocustolearnmoreSubmissionhistory","volume":"30","author":"I Gabriel","year":"2020","unstructured":"Gabriel I (2020) Artificial intelligence, values, and alignment. Minds Mach 30(3):411\u2013437. https:\/\/doi.org\/10.1007\/s11023-020-09539-2FocustolearnmoreSubmissionhistory","journal-title":"Minds Mach"},{"key":"5658_CR68","unstructured":"Hemphill TA (2020) Human Compatible: Artificial Intelligence and the Problem of Control. HeinOnline"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05658-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-05658-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05658-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T13:54:48Z","timestamp":1726667688000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-05658-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,10]]},"references-count":68,"journal-issue":{"issue":"21","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["5658"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-05658-w","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,10]]},"assertion":[{"value":"30 June 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 August 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declaration"}},{"value":"The authors declare no potential conflict of interest. Authors also declare that they have no conflict of interest with the Guest Editorial Board Members.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The study is performed following the ethical rules of Protection Of Research Risks To Humans, Indian Statistical Institute, Kolkata, India.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"The subjects gave their consent.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"The subjects gave their consent regarding publishing the data.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}