Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers.

S Bengesi, H El-Sayed, MK Sarker, Y Houkpati… - IEEE …, 2024 - ieeexplore.ieee.org
The launch of ChatGPT in 2022 garnered global attention, marking a significant milestone in
the Generative Artificial Intelligence (GAI) field. While GAI has been in effect for the past …

Leveraging generative AI for urban digital twins: a sco** review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city …

H Xu, F Omitaomu, S Sabri, S Zlatanova, X Li, Y Song - Urban Informatics, 2024 - Springer
The digital transformation of modern cities by integrating advanced information,
communication, and computing technologies has marked the epoch of data-driven smart city …

Variational autoencoders for data augmentation in clinical studies

D Papadopoulos, VD Karalis - Applied Sciences, 2023 - mdpi.com
Featured Application Variational autoencoders, which are a type of neural network, are
introduced in this study as a means to virtually increase the sample size of clinical studies …

Improvement of the performance of scattering suppression and absorbing structure depth estimation on transillumination image by deep learning

NA Dang Nguyen, HN Huynh, TN Tran - Applied Sciences, 2023 - mdpi.com
The development of optical sensors, especially with regard to the improved resolution of
cameras, has made optical techniques more applicable in medicine and live animal …

[HTML][HTML] Exploring the Potential of Generative Adversarial Networks in Enhancing Urban Renewal Efficiency

Y Lin, M Song - Sustainability, 2024 - mdpi.com
As Chinese cities transition into a stage of stock development, the revitalization of industrial
areas becomes increasingly crucial, serving as a pivotal factor in urban renewal. The …

[HTML][HTML] A Deep Learning-Based Method for Bearing Fault Diagnosis with Few-Shot Learning

Y Li, X Gu, Y Wei - Sensors, 2024 - mdpi.com
To tackle the issue of limited sample data in small sample fault diagnosis for rolling bearings
using deep learning, we propose a fault diagnosis method that integrates a KANs-CNN …

Deep Error-Correcting Output Codes

LN Wang, H Wei, Y Zheng, J Dong, G Zhong - Algorithms, 2023 - mdpi.com
Ensemble learning, online learning and deep learning are very effective and versatile in a
wide spectrum of problem domains, such as feature extraction, multi-class classification and …

The application of artificial intelligence-assisted technology in cultural and creative product design

J Liang - Scientific Reports, 2024 - nature.com
This study proposes a novel artificial intelligence (AI)-assisted design model that combines
Variational Autoencoders (VAE) with reinforcement learning (RL) to enhance innovation and …

Stylized facts of metaverse non-fungible tokens

S Chan, D Chandrashekhar, W Almazloum… - Physica A: Statistical …, 2024 - Elsevier
Abstract Non-Fungible Tokens (NFTs) within the metaverse represent a rapidly emerging
sector in the digital asset space. This paper provides a comprehensive review of the …

Research on designers' behavioral intention toward Artificial Intelligence-Aided Design: integrating the Theory of Planned Behavior and the Technology Acceptance …

J Jiao, X Cao - Frontiers in Psychology, 2024 - frontiersin.org
Artificial Intelligence-Aided Design (AIAD) has numerous advantages and tremendous
benefits for designers. However, not all designers are keen to integrate AIAD into their …