Bibliografie tematiche / Generation

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Letteratura scientifica selezionata sul tema "Generation"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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Articoli di riviste sul tema "Generation"

Keeling, Sarah. "Advising the Millennial Generation." NACADA Journal 23, no. 1-2 (2003): 30–36. http://dx.doi.org/10.12930/0271-9517-23.1-2.30.

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In Generations: The History of America's Future, 1584 to 2069 (1991), William Strauss and Neil Howe articulated their idea of generations. In Millennials Rising: The Next Great Generation 2000, they expanded significantly on the Millennial generation. The first wave of Millennials hit college campuses in the fall of 2000. These students will leave their mark on higher education and academic advising. Academic advisors aware of generational patterns and tendencies will be more effective when working with students. In this article, I discuss the concept of generations, define the Millennial gene

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Möhr, J. R. "The Generation of Generations." Methods of Information in Medicine 24, no. 02 (1985): 55–56. http://dx.doi.org/10.1055/s-0038-1635363.

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FADJAR, Nurman Setiawan, Tyas Danarti HASCARYANI, and Risqi Noor Hidayati PUTRI. "Risk Avoidance In Intergenerational Investment Decisions." International Journal of Environmental, Sustainability, and Social Science 5, no. 3 (2024): 599–605. http://dx.doi.org/10.38142/ijesss.v5i3.1069.

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The character of a generation also shapes risk avoidance behavior. Socio-cultural and economic background influencing each generation's character formation results in differences in the investment preferences and the risk-taking tendencies in each generation group. This research aims to observe the influence of risk avoidance behavior of intergenerational investors on their investment decisions. The sample consisted of 240 respondents, who were obtained through the distribution of research questionnaires. The primary data used in this research is data from behavioral experimental methods for e

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Bhatia, Rahul, Vishakha Gautam, and Yash Kumar Ankush Garg. "Dynamic Question Answer Generator: An Enhanced Approach to Question Generation." International Journal of Trend in Scientific Research and Development Volume-3, Issue-4 (2019): 785–89. http://dx.doi.org/10.31142/ijtsrd23730.

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Shin, Hayoung, and Sungbum Cho. "MZ Generation's Perception of University Evaluation: Focusing on the Difference Between Generations." Korean Society of Culture and Convergence 45, no. 1 (2023): 497–510. http://dx.doi.org/10.33645/cnc.2023.01.45.01.497.

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The purpose of this study is to analyze the awareness about unverisyt of MZ generation (millennials and Z generation) comparing the other generatios, For this study, questions related to awareness, perception, and demand for university evaluation were independently developed, and 1,458 people were randomly sampled across all generations from their 10s to 90s, and a survey was conducted. The MZ generation group of 859 (58.9%) revealed a statistically significant difference in awareness level from other generations regarding the publicity, reliability, and accountability of the university. Throu

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Prasad, Timande Sahil Dhawale Shreyas Waghmare Sanket Dhumane Rushikesh Pimple Kshitij Madpuwar Dr. S. W. Mohod. "Text-to-Image Generation Using Deep Learning." International Journal of Advanced Innovative Technology in Engineering 10, no. 2 (2025): 113–15. https://doi.org/10.5281/zenodo.15407889.

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The Text-to-Image generation tasks has stand out as an innovation in the field of computer vision (CV). Recent innovations and advancements in generative models have led to the development of various text-to-image generation techniques. This paper presents a comprehensive implementation of a text to image generation system leveraging Stable Diffusion, a diffusion based generative model that can produce high-quality images with fine-grained details. The system is integrated with a Flask-based web application, providing users with a user-friendly interface to generate images from textual prompts

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Jean, Nicole H. Bernardo, Earon D.B. Cruz Daniel, Rhoy B. Dela Cruz Sam, et al. "Happy as Larry: A Transgenerational Qualitative Analysis of Happiness." International Journal of Social Science And Human Research 05, no. 12 (2022): 5479–90. https://doi.org/10.5281/zenodo.7417866.

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This academic study aims to know what are the sources of happiness from the perspective of different generations. This research is founded on the Hedonism Theory & Emotional State View, Life Satisfaction Theory & Hybrid Theories, Positive Psychology Theory, Strauss-Howe Generational Theory, and Mannheim’s Theory of Generation. The study was a qualitative research design, a phenomenological approach, a semi-structured interview was used, and purposive sampling. The significant statements were thoroughly examined and organized into themes. It was found that (1) For Generation Alpha

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Wang, Xi Bo, Ya Lin Lei, and Min Yao. "China's Thermal Power Generation Forecasting Based on Generalized Weng Model." Advanced Materials Research 960-961 (June 2014): 503–9. http://dx.doi.org/10.4028/www.scientific.net/amr.960-961.503.

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Since the 21st century, China's power industry has been developing very quickly, and the generated electrical energy has been growing rapidly. Although nuclear power, wind power, solar power generations have been increased, thermal power generation still accounts for more than 80% of the total generating capacity. Thermal power provides an important material basis for the development of the national economy. Therefore, the prediction research on China's thermal power generation trend is becoming a topic of great interest. The fuel of thermal power generation-coal, is an exhaustible resource. D

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DURMAZ, Şerife, and Bülent OKUMUŞ. "GENERATION DIFFERENCES IN BUSINESS LIFE AND GENERATION Z." IEDSR Association 6, no. 16 (2021): 47–68. http://dx.doi.org/10.46872/pj.448.

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For successful interaction and communication to occur in organizations, it is necessary to understand the characteristics of each generation and what motivates them to be successful and good employees. In an organization, many of the employees' values and attitudes towards work can be quite different from previous generations, and managers need to take these generational differences into account in order to effectively manage the workforce. Strauss and Howe (1991) identified eighteen generations throughout four centuries of American history, dating back to the first New World colonizers. In th

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Thasleena, K. Fathimath, and P. Santhi. "Generational Divide in Digital Banking: Comparing Experience and Expectation across Generations X, Y, and Z." Indian Journal of Information Sources and Services 15, no. 2 (2025): 268–74. https://doi.org/10.51983/ijiss-2025.ijiss.15.2.34.

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Digital banking has become a crucial component oftoday's financial environment with its ease of use andaccessibility. How Generation X, Generation Y, and GenerationZ have embraced and changed digital banking is distinct. Thedemands, tastes, and experiences of these generational groupswith digital banking services differ. This study aims to examinedigital banking experience and expectations of customersamong generations X, Y, and Z in the Malabar region of Kerala,which has a rich and diverse cultural heritage. A comprehensiveinterview was conducted with digital banking customers,representing a

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Tesi sul tema "Generation"

Malmaeus, Michelle, and Mehdi Hassan. "Generations Y:s förhållningssätt till arbetslivet : En studie om den nya generationen medarbetare." Thesis, Södertörns högskola, Institutionen för samhällsvetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-28139.

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Syfte: Syftet med studien är att undersöka Generation Y:s förhållningssätt till arbetslivet för att ge en förståelse för deras föreställningar, behov och drivkrafter. Metod: Utgångspunkten är en kvalitativ studie, där fokusgrupper tillämpas för att att kartlägga och skapa förståelse för Generation Y:s förhållningssätt till arbetslivet. Dessa val ligger till grund för studiens utförande och tillvägagångssätt. Resultat & slutsats: Resultatet av fokusgruppsintervjuerna visade på generationens ifrågasättande attityd till arbetssätt och auktoriteter. Fokusgrupperna visade även på ett behov av a

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Sanhueza, Carolina, and Paula Falkevinge. "Generation Z : Den sökande generationen / Generation@ / Netgeneration." Thesis, Stockholms universitet, Institutionen för pedagogik och didaktik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-104751.

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Andledningen till att vi valt att undersöka Generation Z är för att vi som blivande studie- och yrkesvägledare kommer arbeta med dessa ungdomar. Generation Z är fortfarande unga men det hindrar dem inte från att vara uppkopplade på olika sociala medier. Aldrig tidigare har en generation haft så enkelt att hitta vad de söker efter. Den här generationen ligger i vårt intresse eftersom vi som framtida studie- och yrkesvägledare ska mer försöka knyta ihop säcken med all information som ges.<br>The reason that we have chosen to examine Generation Z is that we as a future career counselors will work

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Henningsson, Anna. "Generating Generations - Automatic generation of 3D characters by simulation of genetic inheritance." Thesis, Umeå universitet, Institutionen för datavetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-128414.

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This thesis proposes a model that can simulate multiple generations of genetic inheritance as a way of creating varied 3D content automatically. The proposed model should be less complex and less resource demanding than existing models while producing considerably better results than a model generating content by simple randomization. To achieve variation, the design of the base 3D model for character customization was based on different animation techniques, modiﬁers were based on anthropometry elements from advanced genetic simulations and known cognitive factors important for recognition. B

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Ronnfeldt, Jane. "Generational marketing: Baby boomers, Generation X and the net generation." CSUSB ScholarWorks, 2001. https://scholarworks.lib.csusb.edu/etd-project/2019.

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The purpose of this project is to gain a better understanding of the different market opportunities available to credit unions. The project differentiates the markets by age: Net Generation 2 to 22, Generation X 23 to 34 and the Baby Boomers 35 to 53. Each of these groups are important to the ongoing health of credit unions.

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Govitvatana, Wipanut Venique. "Generation gap in the workplace between Baby Boomers and Generation X." Online version, 2001. http://www.uwstout.edu/lib/thesis/2001/2001govitvatanaw.pdf.

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Wang, Zesen. "Generative Adversarial Networks in Text Generation." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264575.

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The Generative Adversarial Network (GAN) was firstly proposed in 2014, and it has been highly studied and developed in recent years. It has obtained great success in the problems that cannot be explicitly defined by a math equation such as generating real images. However, since the GAN was initially designed to solve the problem in a continuous domain (image generation, for example), the performance of GAN in text generation is developing because the sentences are naturally discrete (no interpolation exists between “hello" and “bye"). In the thesis, it firstly introduces fundamental concepts i

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Björkman, Lovisa, and Elin Myhrman. "Röster från tre generationer : En kvalitativ studie kring generationer på arbetsplatsen." Thesis, Malmö universitet, Malmö högskola, Institutionen för konst, kultur och kommunikation (K3), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-40089.

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Syftet med studien är att undersöka respondenter från Generation X (1964 – 1979), Y (1980 – 1995) och Zs (1996 – 2012) behov och önskemål på arbetsplatsen, vilka positiva och negativa attityder de har mot motivation, relation och arbetsmiljö. Studien har genomförts genom en kvalitativ undersökning, innehållsanalys i form av tematisering och genom att använda tidigare forskning kring generationer. Den kvalitativa metoden var intervjuer med 12 respondenter, varav fyra var från vardera generation. Modeller såsom Maslows behovstrappa, tvåfaktorteorin och förstärkningsteorin används i studien. Stud

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El, Chababi Maria. "Are They Really Different? The Entrepreneurial Processes from the Perspective of Different Generations of Immigrant Entrepreneurs." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31692.

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Immigrant entrepreneurship is defined as business establishment and ownership among immigrants who arrive to a new host country. Immigrant entrepreneurship has become an important theme due to the increasing rates of immigration to developed countries, and its impact on their economic development. However it is also discredited and qualified as low value-added, rarely innovative, restricted to the ethnic communities and with stagnating growth potential. Following this debate, a new research stream affirms that immigrants should not be treated as one entity. Thus attention is shifting towards g

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Berman, Alan. "Generative adversarial networks for fine art generation." Master's thesis, University of Cape Town, 2020. http://hdl.handle.net/11427/32458.

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Generative Adversarial Networks (GANs), a generative modelling technique most commonly used for image generation, have recently been applied to the task of fine art generation. Wasserstein GANs and GANHack techniques have not been applied in GANs that generate fine art, despite their showing improved GAN results in other applications. This thesis investigates whether Wasserstein GANs and GANHack extensions to DCGANs can improve the quality of DCGAN-based fine art generation. There is also no accepted method of evaluating or comparing GANs for fine art generation. DCGAN's, Wasserstein GANs' and

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Sorkhei, Moein. "Conditional Generative Flow for Street Scene Generation." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288891.

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Generative modeling is a major branch of machine learning attributed to designing models that can learn how data are generated and hence are able to synthesize novel data. With the recent advancements in deep learning, generative models have been improved significantly and successfully applied in a variety of domains, including computer vision, video generation, audio generation, and even in medical applications. Amongst different categories of generative models, GAN-based models [1] are by far the most well-known generative models applied to a variety of computer vision tasks due to their abi

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Libri sul tema "Generation"

Becker, H. A. De toekomst van de verloren generatie. Meulenhoff, 1997.

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Sandra, Martz, and Coe Shirley 1956-, eds. Generation to generation. Papier-Mache Press, 1998.

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Ryan, Maureen. Generation to generation. Cassell Educational, 1992.

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O'Connor, Maureen. Generation to generation. Cassell, 1993.

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O'Connor, Maureen. Generation to generation. Cassell in association with the LinkAge Trust, 1993.

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Leigh, Claire, and Joel Mullan. Generation crisis: Promoting justice between generations. Fabian Society, 2012.

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McCrindle, Mark. The ABC of XYZ: Understanding the global generations. UNSW Press, 2009.

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Illies, Florian. Generation Golf: Eine Inspektion. 3rd ed. Argon, 2000.

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Merrell, James L. From generation to generation. Christian Board of Publication, 1992.

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Tomasov, Agnes. From generation to generation. Azrieli Foundation, 2010.

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Capitoli di libri sul tema "Generation"

Kanz, Christine. "Generation — Generatio — Verwandtschaft." In Kleist-Jahrbuch 2010. J.B. Metzler, 2010. http://dx.doi.org/10.1007/978-3-476-00563-2_13.

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Bala, Ram, Natarajan Balasubramanian, and Amit Joshi. "The Generative Generation." In The AI-Centered Enterprise. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003541561-2.

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Einramhof-Florian, Helene. "Generation Corona, Generation Krise, Generation Lockdown, Generation Dauerkrise, Generation Aufbruch." In Fit für die jungen Generationen am Arbeitsplatz. Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-39149-2_5.

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Rose, Ray J. "Generation Upon Generation." In DNA Know Thyself. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8381-6_7.

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Mao, Xudong, and Qing Li. "GANs for Image Generation." In Generative Adversarial Networks for Image Generation. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-33-6048-8_2.

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Rabe-Kleberg, Ursula. "Von Generation zu Generation?" In Bildungsreform als Sozialreform. VS Verlag für Sozialwissenschaften, 2005. http://dx.doi.org/10.1007/978-3-322-91642-6_6.

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Siritsky, Nachshon. "From Generation to Generation." In Reframing Trauma Through Social Justice. Routledge, 2024. http://dx.doi.org/10.4324/9781003379591-11.

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Arnold, Ludwig. "Generation." In Springer Monographs in Mathematics. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-12878-7_2.

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Steinbach, Anja. "Generation." In Grundbegriffe der Soziologie. Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-20978-0_26.

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Peck, Stewart B., Carol C. Mapes, Netta Dorchin, et al. "Generation." In Encyclopedia of Entomology. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_1053.

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Atti di convegni sul tema "Generation"

Djordjevic, Sophie, Ralf Behr, and Wilfrid Poirier. "Next generation Programmable Quantum Current Generator." In 2024 Conference on Precision Electromagnetic Measurements (CPEM). IEEE, 2024. http://dx.doi.org/10.1109/cpem61406.2024.10646087.

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Guo, Yihan, Tingwen Liu, Jiawei Sheng, Duohe Ma, Ming Sun, and Ling Tian. "Translational Generative Retrieval via Potential Query Generation." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10888918.

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Aly, Karim, and Alexei Sharpanskykh. "Synthetic Flight Data Generation Using Generative Models." In 2025 Integrated Communications, Navigation and Surveillance Conference (ICNS). IEEE, 2025. https://doi.org/10.1109/icns65417.2025.10976960.

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Yang, Yue, Yueyue Hu, Hanchi Ren, Yunying Wang, Jingjing Deng, and Xianghua Xie. "Spatial layout generation via generative adversarial networks." In International Conference on AI-generated Content (AIGC 2024), edited by Duoqian Miao and Feng Zhao. SPIE, 2025. https://doi.org/10.1117/12.3065211.

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Huo, Chao, Cheng Peng, Zhiguo Hao, Xiuting Rong, Xuetao Dong, and Songhao Yang. "Scenario Generation Method Considering the Uncertainty of Renewable Energy Generations Based on Generative Adversarial Networks." In 2024 3rd International Conference on Energy and Electrical Power Systems (ICEEPS). IEEE, 2024. http://dx.doi.org/10.1109/iceeps62542.2024.10693230.

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Vinothkumar, S., S. Varadhaganapathy, R. Shanthakumari, S. Dhanushya, S. Guhan, and P. Krisvanth. "Utilizing Generative AI for Text-to-Image Generation." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725454.

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Ding, Keyu, Yongcan Wang, Zihang Xu, Zhenzhen Jia, and Enhong Chen. "Generative Input: Towards Next-Generation Input Methods Paradigm." In Findings of the Association for Computational Linguistics ACL 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-acl.218.

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Hayawi, Kadhim, Sakib Shahriar, and Hakim Hacid. "On Digital Art Generation Using Generative Adversarial Networks." In 2024 International Conference on Electrical, Computer and Energy Technologies (ICECET). IEEE, 2024. http://dx.doi.org/10.1109/icecet61485.2024.10698003.

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Tikas, Evangelos, Lazaros Alexios Iliadis, Sotirios Sotiroudis, et al. "Human Blastocyst Image Generation Using Generative Adversarial Networks." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635904.

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Zhang, Boyu, Xin Wang, and Kai Liu. "Generative Model for Node Generation." In ICCAI '20: 2020 6th International Conference on Computing and Artificial Intelligence. ACM, 2020. http://dx.doi.org/10.1145/3404555.3404599.

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Rapporti di organizzazioni sul tema "Generation"

Adams, D. J., and S. G. Berenyi. Turbine-generator set development for power generation. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/656889.

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Yamashiro, Neil. Generation X. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada344977.

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Xu, Xiaowei. Generation COVID. The IFS, 2020. http://dx.doi.org/10.1920/ps.ifs.2024.0192.

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David, Patty. Generation X Snapshots. AARP Research, 2015. http://dx.doi.org/10.26419/res.00116.000.

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David, Patty. Generation X Demographics. AARP Research, 2015. http://dx.doi.org/10.26419/res.00116.001.

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David, Patty. Generation X Finances. AARP Research, 2015. http://dx.doi.org/10.26419/res.00116.002.

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David, Patty. Generation X Health. AARP Research, 2015. http://dx.doi.org/10.26419/res.00116.003.

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David, Patty. Generation X Technology. AARP Research, 2015. http://dx.doi.org/10.26419/res.00116.004.

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Zhao, Zilai, and Charles Gough. Next Generation Inverter. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1261839.

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Souers, P. C. New generation detonics. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/515977.

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