AccScience Publishing / AC / Online First / DOI: 10.36922/ac.2282
Submit to AC
Cite this article
41
Download
1322
Views
Journal Browser
Volume | Year
Issue
Search
Forthcoming Issue
Current Issue
View All
News and Announcements
View All
ARTICLE

Computer vision in tactical artificial intelligence art

Dejan Grba1*
Show Less
1 Digital Art Program, Interdisciplinary Graduate Center, University of the Arts, Belgrade, Serbia
AC 2024, 2(3), 2282 https://doi.org/10.36922/ac.2282
Submitted: 20 November 2023 | Accepted: 17 May 2024 | Published: 13 August 2024
© 2024 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Download PDF
Cite
XML
Abstract

Artificial intelligence (AI) art comprises a spectrum of creative endeavors that emerge from and respond to the development of AI, the expansion of AI-powered economies, and their influence on culture and society. Within this repertoire, the relationship between the cognitive value of human vision and the wide application range of computer vision (CV) technologies opens a sizeable space for exploring the problematic sociopolitical aspects of automated inference and decision-making in modern AI. This paper examines art practices critically engaged with the notions and protocols of CV. After identifying and contextualizing CV-related tactical AI art, we discuss the features of exemplar artworks in four interrelated subject areas. Their topical overlaps, common critical points, and shared pitfalls plot a wider landscape of tactical AI art, allowing us to detect factors that affect its poetic cogency, social responsibility, and political impact, some of which are rooted in the theoretical premises of digital art activism. Along these lines, the paper outlines the routes for addressing the challenges and advancing the field.

Keywords
Artificial intelligence
Biometric AI
Computational art
Computer vision
Machine vision
Tactical AI art
Taxonomic imaging
Funding
None.
Conflict of interest
The author declares that he has no competing interests.
References
  1. Cetinić E, She J. Understanding and creating art with Ai: Review and outlook. ACM Trans Multimed Comput Commun Appl. 2022;18(2):1-22. doi: 10.1145/3475799

 

  1. Grba D. Deep else: A critical framework for AI Art. MDPI Digit. 2022;2(1):1-32. doi: 10.3390/digital2010001

 

  1. Webb A, Caufield E, Grau E, Alsever J, Cooney C,Blake M. 2022 Tech Trends Report: Artificial Intelligence. 15th ed. Future Today Institute; 2022. Available from: https://futuretodayinstitute.com/mu_uploads/2022/03/fti_tech_trends_2022_book01.pdf [Last accessed on 2024 Apr 05].

 

  1. O’Neil C. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Kindle edition. New York, NY: Crown; 2016.

 

  1. Zuboff S. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York, NY: Public Affairs; 2019.

 

  1. Raley R. Tactical Media. Minneapolis, MN: University of Minnesota Press; 2009.

 

  1. Grba D. Lures of Engagement: An Outlook on Tactical AI Art. In: Verdicchio M, Carvalhais M, RIbas L, Rangel A, editors. Proceedings of xCoAx 2022, 10th Conference on Computation, Communication, Aesthetics & X, Porto: i2ADS Research Institute in Art, Design and Society; 2022. p. 58-74. doi: 10.24840/xCoAx_2022_39

 

  1. Marcus GF, Davis E. Rebooting AI: Building Artificial Intelligence We Can Trust. New York, NY: Pantheon Books; 2019.

 

  1. Mitchell M. Artificial Intelligence: A Guide for Thinking Humans. Kindle edition. New York, NY: Farrar, Straus and Giroux; 2019.

 

  1. Larson EJ. The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do. Cambridge/London, UK: The Belknap Press of Harvard University Press; 2021.

 

  1. Pasquinelli M. How a machine learns and fails-a grammar of error for artificial intelligence. Spheres J Digit Cult. 2019;5:1-17.

 

  1. Kearns M, Roth A. The Ethical Algorithm: The Science of Socially Aware Algorithm Design. Oxford, UK: Oxford University Press; 2019.

 

  1. Christian B. The Alignment Problem: Machine Learning and Human Values. New York, NY: W. W. Norton & Company, Inc.; 2020.

 

  1. Crawford K. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven, CT, London, UK: Yale University Press; 2021.

 

  1. Natale S. Deceitful Media: Artificial Intelligence and Social Life After the Turing Test. New York, NY: Oxford University Press; 2021.

 

  1. Joler V, Pasquinelli M. The Nooscope Manifested: Artificial Intelligence as Instrument of Knowledge Extractivism. Project Website; 2021. Available from: https://nooscope.ai [Last accessed on 2024 Apr 05].

 

  1. Roberge J, Castelle M, editors. The Cultural Life of Machine Learning: An Incursion into Critical AI Studies. London, UK: Palgrave Macmillan/Springer Nature; 2021.

 

  1. Raley R, Rhee J, editors. Critical AI: A field in formation. Am Lit J. 2023;95(2): 185-204. doi: 10.1215/00029831-10575021

 

  1. Żylińska J. AI Art: Machine Visions and Warped Dreams. London, UK: Open Humanities Press; 2020.

 

  1. Zeilinger M. Tactical Entanglements: AI Art, Creative Agency, and the Limits of Intellectual Property. Lüneburg, DE: Meson Press; 2021.

 

  1. Grba D. Brittle Opacity: Ambiguities of the Creative AI. In: Verdicchio M, Carvalhais M, Ribas L, Rangel A, editors. Proceedings of xCoAx 2021, 9th Conference on Computation, Communication, Aesthetics & X, Porto: i2ADS Research Institute in Art, Design and Society; 2021. p. 235-260. doi: 10.5281/zenodo.5831884

 

  1. Grba D. Renegade X: Poetic Contingencies in Computational Art. In: Carvalhais M, Verdicchio M, Ribas L, Rangel A, editors. Proceedings of xCoAx 2023, 11th Conference on Computation, Communication, Aesthetics & X, Porto: i2ADS Research Institute in Art, Design and Society; 2023. p. 201-221.

 

  1. Grba D. Faux semblants: A critical outlook on the commercialization of digital art. MDPI Digit. 2023;3(1):67-80. doi: 10.3390/digital3010005

 

  1. Davies ER. Computer Vision: Principles, Algorithms, Applications, Learning. 5th ed. London, UK: Academic Press; 2018.

 

  1. Kubovy M. The Psychology of Perspective and Renaissance Art. Cambridge, UK: Cambridge University Press; 1988.

 

  1. STOA (Scientific Foresight Unit). The Historical Relationship between Artistic Activities and Technology Development. European Parliamentary Research Service; 2019. Available from: https://www.europarl.europa.eu/regdata/etudes/idan/2019/634439/eprs_ida(2019)634439_en.pdf [Last accessed on 2024 Apr 05].

 

  1. Witcombe CLCE. Art History and Technology: A Brief History. Christopher L.C.E. Witcombe’s Website; n.d. Available from: https://arthistoryresources.net/arth-technology/arthtechnology1.html [Last accessed on 2024 Apr 05].

 

  1. Surveillance Art; 2023. Available from: https://en.wikipedia.org/wiki/surveillance_art [Last accessed on 2024 Apr 05].

 

  1. Foucault M. Discipline and Punish: The Birth of the Prison. New York, NY: Vintage Books; 1995.

 

  1. Levin TY, Frohne U, Weibel P. CTRL [SPACE], Rhetorics of Surveillance from Bentham to Big Brother. Karlsruhe, DE: ZKM/Cambridge, UK: The MIT Press; 2002.

 

  1. Remes O, Skelton P, editors. Conspiracy Dwellings: Surveillance in Contemporary Art. Newcastle upon Tyne, UK: Cambridge Scholars Publishing; 2010.

 

  1. Harding JM. Performance, Transparency, and the Cultures of Surveillance. Ann Arbor, MI: University of Michigan Press; 2018.

 

  1. Krueger M. Videoplace. Weebly Website; 1975. Available from: https://aboutmyronkrueger.weebly.com/videoplace.html [Last accessed on 2024 Apr 05].

 

  1. Bureau of Inverse Technology. Suicide Box. Bureau of Inverse Technology Website; 1996. Available from: https://www.bureauit.org/sbox [Last accessed on 2024 Apr 05].

 

  1. Shachtman N. Tech and Art Mix at RNC Protest. Wired News; 2004. Available from: https://archive.ph/4LQi#selection-809.8-817.348 [Last accessed on 2024 Apr 05].

 

  1. Levin G, Baltus G. Opto-Isolator. Golan Levin’s Website Archive; 2007. Available from: https://www.flong.com/archive/projects/optoisolator/index.html [Last accessed on 2024 Apr 05].

 

  1. YCAM. Seiko Mikami: Desire of Codes. YCAM InterLab Website; 2010. Available from: https://special.ycam.jp/interlab/en/develop/2010/desire-of-codes.html [Last accessed on 2024 Apr 05].

 

  1. Gates KA. Our Biometric Future: Facial Recognition Technology and the Culture of Surveillance. New York, NY: New York University Press; 2011.

 

  1. Moeller C. Cheese. Christian Moeller’s Website; 2003. Available from: https://christianmoeller.com/Cheese [Last accessed on 2024 Apr 05].

 

  1. Margolles T. Santiago Sierra. BOMB Magazine; 2004. p. 86. Available from: https://bombmagazine.org/articles/santiago-sierra [Last accessed on 2024 Apr 05].

 

  1. Cirio P. Networked reality flow hacks. In: DeLaure M, Fink M, editors. Culture Jamming: Activism and the Art of Cultural Resistance. New York, NY: New York University Press; 2017. p. 423-426.

 

  1. McDonald K. Sharing Faces. Kyle McDonald’s Vimeo Collection; 2014. Available from: https://vimeo.com/96549043 [Last accessed on 2024 Apr 05].

 

  1. Peterhaensel A. Smile to Vote: Towards Political Physiognomy Analytics - Predicting Electoral Behavior from Live Video. Proceedings of ISEA, the 24th International Symposium on Electronic Art. Durban: Faculty of Arts and Design, Durban University of Technology; 2018. p. 79-85. Available from: https://smiletovote.com [Last accessed on 2024 Apr 05].

 

  1. Guljajeva V, Cane M. Keep Smiling. Project Website; 2022. Available from: https://keepsmiling.var-mar.info [Last accessed on 2024 Apr 05].

 

  1. Guljajeva V, Cane M. Keep smiling. In: Verdicchio M, Carvalhais M, Ribas L, Rangel A, editors. Proceedings of xCoAx 2022, 10th Conference on Computation, Communication, Aesthetics & X. Porto, PRT: i2ADS Research Institute in Art, Design and Society; 2022. p. 340-346. doi: 10.24840/xCoAx_2022_66

 

  1. Taylor A. The Automation Charade. Logic, 5 (Failure); 2018. Available from: https://logicmag.io/failure/the-automationcharade [Last accessed on 2024 Apr 05].

 

  1. Vogelaar C. Random String of Emotions. Coralie Vogelaar’s Website; 2018. Available from: https://coralievogelaar.com/random-string-of-emotion-artist-publication [Last accessed on 2024 Apr 05].

 

  1. Wang CS. An Interview with ALEX. Project website; 2020. Available from: https://theinterview.ai [Last accessed on 2024 Apr 05].

 

  1. Rinaldo K. Paparazzi Bots. Ken Rinaldo’s Website; 2022. Available from: https://www.kenrinaldo.com/portfolio/paparazzi-bots [Last accessed on 2024 Apr 05].

 

  1. Shinseungback Kimyonghun. Nonfacial Mirror. Shinseungback Kimyonghun’s website; 2013. Available from: https://ssbkyh.com/works/nonfacial_mirror [Last accessed on 2024 Apr 05].

 

  1. Weibel P. Observing Observation: Uncertainty. The ZKM. Center for Art and Media Karlsruhe Website; 1973. Available from: https://zkm.de/en/node/37000 [Last accessed on 2024 Apr 05].

 

  1. Okada K, Fujimoto N. Peeping Hole. Kenichi Okada’s Website; 2010. Available from: https://www.kenichiokada.com/projects/2010/peepinghole.html [Last accessed on 2024 Apr 05].

 

  1. McDonald K, Mets M. Blind Self Portrait. Kyle McDonald’s Vimeo Collection; 2012. Available from: https://vimeo.com/44489751 [Last accessed on 2024 Apr 05].

 

  1. Rodcorp. William Anastasi: Subway Drawings. Rodcorp Blog; 2004. Available from: https://rodcorp.typepad.com/rodcorp/2004/06/william_anastas.html [Last accessed on 2024 Apr 05].

 

  1. Tresset P. Human Studies. Patrick Tresset’s Website; 2019. Available from: https://patricktresset.com [Last accessed on 2024 Apr 05].

 

  1. Stocker G, Jandl M, Hirsch AJ, editors. The Practice of Art and AI, 217. Berlin, DE: Hatje Cantz Verlag; 2021.

 

  1. Grosser B. Computers Watching Movies. Ben Grosser’s Website; 2013. Available from: https://bengrosser.com/projects/computers-watching-movies [Last accessed on 2024 Apr 05].

 

  1. Richardson M. Descriptive CameraTM. Matt Richardson’s Website; 2012. Available from: http://mattrichardson.com/descriptive-camera/index.html [Last accessed on 2024 Apr 05].

 

  1. Johnson D, Verdicchio M. Reframing AI discourse: Minds and machines. UWS Acad Portal. 2017;27(4):575-590. doi: 10.1007/s11023-017-9417-6

 

  1. Gray ML, Suri S. Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass, 2–7. Boston, MA and New York, NY: Houghton Mifflin Harcourt; 2019.

 

  1. Paulsen K. Shitty automation: Art, artificial intelligence,humans in the loop. Media-N J N Media Caucus. 2020;16(1):4-23.

 

  1. Elwes J. Machine Learning Porn. Jake Elwes’ Website; 2016. Available from: https://www.jakeelwes.com/project-mlporn.html [Last accessed on 2024 Apr 05].

 

  1. Riccio P, Oliver JL, Escolano F, Oliver N. Algorithmic Censorship of Art: A Proposed Research Agenda. In: Proceedings of the 11th International Conference on Computational Creativity; 2022. Available from: https://computationalcreativity.net/iccc22/wp-content/uploads/2022/06/iccc-2022_17s_riccio-et-al.pdf [Last accessed on 2024 Apr 05].

 

  1. Elwes J. Closed Loop. Jake Elwes’ Website; 2017. Available from: https://www.jakeelwes.com/project-closedLoop.html [Last accessed on 2024 Apr 05].

 

  1. Shinseungback Kimyonghun. Mind. Shinseungback Kimyonghun’s Website; 2019. Available from: https://ssbkyh.com/works/mind [Last accessed on 2024 Apr 05].

 

  1. Lozano-Hemmer R. Level of Confidence. Rafael Lozano- Hemmer’s Website; 2015. Available from: https://www.lozano-hemmer.com/level_of_confidence.php [Last accessed on 2024 Apr 05].

 

  1. Zer-Aviv M. The Normalizing Machine. Mushon Zer-Aviv’s Website; 2018. Available from: https://mushon.com/tnm [Last accessed: 2024 Apr 05].

 

  1. Mitchell M. Artificial Intelligence: A Guide for Thinking Humans, 88-90. Kindle edition. New York, NY: Farrar, Straus and Giroux; 2019.

 

  1. Kearns M, Roth A. The Ethical Algorithm: The Science of Socially Aware Algorithm Design, 32-48. Oxford, UK: Oxford University Press; 2019.

 

  1. Pasquinelli M. Abnormal Encephalization in the Age of Machine Learning. e-flux; 2016. Available from: https://worker01.e-flux.com/pdf/article_9009069.pdf [Last accessed on 2024 Apr 05].

 

  1. Orcutt M. Are Face Recognition Systems Accurate? Depends on Your Race. MIT Technology Review Website; 2016. Available from: https://www.technologyreview.com/2016/07/06/158971/are-face-recognition-systemsaccurate-depends-on-your-race [Last accessed on 2024 Apr 05].

 

  1. Buolamwini J, Gebru T. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification, In: Friedler SA, Wilson C, editors. Proceedings of the 1st Conference on Fairness, Accountability and Transparency

 

  1. 81. New York; 2018. p. 77-91. Available from: https://proceedings.mlr.press/v81/buolamwini18a.html [Last accessed on 2024 Apr 05].

 

  1. Gershgorn D. How a 2018 Research Paper Led Amazon, Microsoft, and IBM to Curb Their Facial Recognition Programs. OneZero Medium website; 2020. Available from: https://onezero.medium.com/how-a-2018-research-paperled-to-amazon-and-ibm-curbing-their-facial-recognitionprograms-db9d6cb8a420 [Last accessed on 2024 Apr 05].

 

  1. Crawford K, Paglen T. Excavating AI: The Politics of Training Sets for Machine Learning. Project website; 2019. Available from: https://excavating.ai [Last accessed on 2024 Apr 05].

 

  1. Kuesel C. An Online Image Database Will Remove 600,000 Pictures After an Art Project Revealed the System’s Racist Bias; 2019. Available from: https://www.artsy.net/article/artsy-editorial-online-image-database-will-remove-600–000-pictures-art-project-revealed-systems-racist-bias [Last accessed on 2024 Apr 05].

 

  1. Arpteg A. Reflections on the ImageNet Roulette Provocation; 2019. Available from: https://www.linkedin.com/pulse/reflections-imagenet-roulette-provocation-anders-arpteg [Last accessed on 2024 Apr 05].

 

  1. Yang K, Qinami K, Fei-Fei L, Deng J, Russakovsky O. Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy. ImageNet website; 2019. Available from: https://image-net.org/update-sep-17-2019.php [Last accessed 2024 Apr 05].

 

  1. Lyons MJ. Excavating ‘Excavating AI’: The Elephant in the Gallery. arXiv preprint; 2020. Available from https://arxiv.org/abs/2009.01215 [Last accessed on 2024 Apr 05].

 

  1. Leibowicz C, Saltz E, Coleman L. Creating AI art responsibly: A field guide for artists. Diseña. 2021;19:5. doi: 10.7764/disena.19.Article.5

 

  1. Lossin RH. Trevor Paglen’s Unstable Truths. e-flux Criticism; 2023. Available from: https://editor.e-flux-systems.com/files/544198_e-flux-criticism-trevor-paglen-s-unstabletruths.pdf [Last accessed on 2024 Apr 05].

 

  1. Groß B, Lee J. The Aerial Bold Project. Benedikt Groß’s Website; 2016. Available from https://benedikt-gross.de/projects/the-aerial-bold-project [Last accessed on 2024 Apr 05].

 

  1. Wilner RG. Pareidolia and the pitfalls of subjective interpretation of ambiguous images in art history. Leonardo. 2021;54(6):638-642.

 

  1. Gradecki J, Curry D. Boogaloo Bias. Project website; 2022. Available from https://www.boogaloo-bias.art [Last accessed on 2024 Apr 05].

 

  1. Larson EJ. The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do, 76-83. Cambridge/London, UK: The Belknap Press of Harvard University Press; 2021.

 

  1. Schmieg S. Decisive Camera. Sebastian Schmieg’s website; 2018. Available from: https://sebastianschmieg.com/decisive-camera [Last accessed on 2024 Apr 05].

 

  1. Schmieg S. Decisive Mirror. Sebastian Schmieg’s website; 2019. Available from: https://sebastianschmieg.com/decisive-mirror [Last accessed on 2024 Apr 05].

 

  1. Zeilinger M. Tactical Entanglements: AI Art, Creative Agency, and the Limits of Intellectual Property, 51-55. Lüneburg, DE: Meson Press; 2021

 

  1. Basanta A. All We’d Ever Need Is One Another. Adam Basanta’s website; 2018. Available from: https://adambasanta.com/allwedeverneed [Last accessed on 2024 Apr 05].

 

  1. Zeilinger M. Tactical Entanglements: AI Art, Creative Agency, and the Limits of Intellectual Property, 94-108. Lüneburg, DE: Meson Press; 2021.

 

  1. Curry D. Artistic defamiliarization in the age of algorithmic prediction. Leonardo. 2023;56(2):177-182.

 

  1. Smil V. Invention and Innovation: A Brief History of Hype and Failure. Cambridge, MA: The MIT Press; 2023. p. 157-165.

 

  1. Żylińska J. AI Art: Machine Visions and Warped Dreams, 75-85. London, UK: Open Humanities Press; 2020

 

  1. Taylor GD. When the Machine Made Art: The Troubled History of Computer Art. New York, NY and London, UK: Bloomsbury Press; 2014.

 

  1. Grba D. Renegade X: Poetic Contingencies in Computational Art. In: Carvalhais M, Verdicchio M, Ribas L, Rangel A, editors. In: Proceedings of xCoAx 2023, 11th Conference on Computation, Communication, Aesthetics & X, Porto: i2ADS Research Institute in Art, Design and Society; 2023. p. 211-213.

 

  1. Grba D. Deep else: A critical framework for AI Art. MDPI Digit. 2022;2(1): 20-21. doi: 10.3390/digital2010001

 

  1. Quaranta D. Between Hype Cycles and the Present Shock: Art at the End of the Future. DOC#6. Nero Publications; 2020. Available from: https://www.neroeditions.com/docs/between-hype-cycles-and-the-present-shock [Last accessed on 2024 Apr 05].

 

  1. Barranha H, Henriques JS, editors. Art, Museums and Digital Cultures: Rethinking Change. Lisbon, PRT: IHA/ NOVA FCSH and Maat; 2021.

 

  1. Lossin RH. Refik Anadol’s ‘Unsupervised’. e-flux Criticism; 2022. Available from: https://www.e-flux.com/criticism/527236/refik-anadol-s-unsupervised [Last accessed on 2024 Apr 05].

 

  1. Raley R. Tactical Media, 30. Minneapolis, MN: University of Minnesota Press; 2009.

 

  1. Barbrook R, Cameron A. The Californian ideology. Science Cult. 1996;6(1):44-72.

 

  1. Lovink G, Rossiter N. Dawn of the Organised Networks. Scottsdale, AZ: Nettime; 2005.

 

  1. Powles J. The Seductive Diversion of ‘Solving’ Bias in Artificial Intelligence. Medium OneZero; 2018. Available from: https://onezero.medium.com/the-seductive-diversion-of-solvingbias-in-artificial-intelligence-890df5e5ef53 [Last accessed on 2024 Apr 05].

 

  1. Curry D. Artistic defamiliarization in the age of algorithmic prediction. Leonardo. 2023;56(2): 180 and passim.

 

  1. Golumbia D. The Cultural Logic of Computation. Cambridge, MA: Harvard University Press; 2009.

 

  1. Zeilinger M. Tactical Entanglements: AI Art, Creative Agency, and the Limits of Intellectual Property, 50-51. Lüneburg, DE: Meson Press; 2021.

 

  1. Galloway AR. Protocol: How Control Exists after Decentralization. Cambridge, MA: MIT Press; 2004. p. 17.

 

  1. Wark M. A Hacker Manifesto. Cambridge: Harvard University Press; 2004.

 

  1. Oliver J, Savičić G, Vasiliev D. The Critical Engineering Manifesto. ZKM website; (n.d.). Available from: https://zkm.de/en/the-critical-engineering-manifesto [Last accessed on 2024 Apr 05].

 

  1. de Certeau M. The Practice of Everyday Life. Berkeley: University of California Press; 2011.

 

  1. Golumbia D. The Cultural Logic of Computation, 24-25. Cambridge, MA: Harvard University Press; 2009.

 

  1. Curtis A. Bitter Lake. Written and directed by Adam Curtis. BBC; 2015. Available from: https://www.bbc.co.uk/programmes/p02gyz6b [Last accessed on 2024 Apr 05].

 

  1. Grba D. Deep else: A critical framework for AI Art. MDPI Digit. 2022;2(1):24. doi: 10.3390/digital2010001

 

  1. Pasquinelli M. How a machine learns and fails-a grammar of error for artificial intelligence. Spheres J Digit Cult. 2019;5:1-17.

 

  1. Grba D. Deep else: A critical framework for AI Art. MDPI Digit. 2022;2(1):24-25. doi: 10.3390/digital2010001
Share
Back to top
Arts & Communication, Electronic ISSN: 2972-4090 Published by AccScience Publishing
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here
Accept