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Akademický článek

Recent Advances in Text-to-Image Synthesis: Approaches, Datasets and Future Research Prospects

Autor: Yong Xuan Tan, Chin Poo Lee, Mai Neo, Kian Ming Lim, Jit Yan Lim, Ali Alqahtani

Publikováno v: IEEE Access, Vol 11, Pp 88099-88115 (2023)

Text-to-image synthesis is a fascinating area of research that aims to generate images based on textual descriptions. The main goal of this field is to generate images that match the given textual description in terms of both semantic consistency and

Externí odkaz: https://doaj.org/article/45abbef8e7a44dceb9cebd3b9653c704

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Akademický článek

Enhanced Text-to-Image Synthesis With Self-Supervision

Autor: Yong Xuan Tan, Chin Poo Lee, Mai Neo, Kian Ming Lim, Jit Yan Lim

Publikováno v: IEEE Access, Vol 11, Pp 39508-39519 (2023)

The task of Text-to-Image synthesis is a difficult challenge, especially when dealing with low-data regimes, where the number of training samples is limited. In order to address this challenge, the Self-Supervision Text-to-Image Generative Adversaria

Externí odkaz: https://doaj.org/article/5ababde7aa254cb8b7da4faefe7c60f7

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Akademický článek

Enhancing Students’ Online Learning Experiences with Artificial Intelligence (AI): The MERLIN Project

Autor: Mai Neo, Chin Poo Lee, Heidi Yeen-Ju Tan, Tse Kian Neo, Yong Xuan Tan, Nazi Mahendru, Zahra Ismat

Publikováno v: International Journal of Technology, Vol 13, Iss 5, Pp 1023-1034 (2022)

The COVID-19 pandemic led to all institutions of education having to transition to fully online learning almost immediately. However, research showed that online learning still lacked adequate interactions with students. This is even more problema

Externí odkaz: https://doaj.org/article/9c02dfe79e5d429fa329d1c94ba22cb3

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