Results 111 to 120 of about 2,911,065 (235)

Evolution and Breakthroughs of Generative Adversarial Network Technology [PDF]

ITM Web of Conferences
Generative Adversarial Networks (GANs) have significantly evolved since their introduction, continually adapting through theoretical and architectural innovations to remain a vibrant research area in generative AI.
Wang Yiding
doaj   +1 more source

PC-GANs: Progressive Compensation Generative Adversarial Networks for Pan-sharpening

, 2022
The fusion of multispectral and panchromatic images is always dubbed pansharpening. Most of the available deep learning-based pan-sharpening methods sharpen the multispectral images through a one-step scheme, which strongly depends on the reconstruction ...
Xing, Yinghui, Zhang, Yanning, Yang, Shuyuan, Wang, Song, Zhang, Yan   +4 more
core  

When Do Robots Go Green? Unveiling Mechanisms, Thresholds, and Spillovers of Industrial Robotics on Global Ecological Capacity

Business Strategy and the Environment, EarlyView.
ABSTRACT This paper examines the relationship between industrial robotics adoption and ecological capacity, measured by biocapacity, using panel data from 50 countries over the period 2000–2024. We investigate the transmission mechanisms, non‐linearities, spatial spillovers, and heterogeneity characterizing this relationship.
Brahim Bergougui, Hamid Ghazi H. Sulimany   +1 more
wiley   +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Generative Adversarial Networks GAN Overview

Jisuanji kexue yu tansuo, 2020
As a new unsupervised learning algorithm framework, generative adversarial networks (GAN) has been favored by more and more researchers, and it has become a research hotspot. GAN is inspired by the two-person zero-sum game theory in game theory. Its unique confrontation training idea can generate high-quality samples and has more powerful feature ...
openaire   +1 more source

A Novel Electromagnetic Sensing Generative Adversarial Network for Uniaxial Objects

Electromagnetic imaging achieves enhanced resolution by leveraging the advanced sensing and data analysis capabilities of Internet of Things (IoT) systems.
Chiu, Chien-Ching;Chen, Po-Hsiang;Jiang, Hao;Shi, Bo-Yu
core   +1 more source

Generative Models in Inorganic Crystals Discovery and Inverse Design

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Generative inverse‐design samples from the vast inorganic crystal design space by starting from target properties such as band gap, stability, and ion transport. This Review examines the representations, generative models, and validation workflows needed to translate candidate structures into stable, potentially synthesizable materials for applications
Tao Li, Xiaolin Liu, Fei Wang, Yan Xiong, Yu Chen, Yan Zhao   +5 more
wiley   +1 more source

Artificial Intelligence in Ophthalmology: From Methodological Advances to Clinical Translation and Future Directions

Eye &ENT Research, EarlyView.
ABSTRACT Artificial intelligence (AI) is reshaping ophthalmology from task‐specific image analysis toward multimodal, longitudinal, and clinically integrated decision support. This narrative review summarizes the methodological evolution of ophthalmic AI, including traditional machine learning, task‐specific deep learning, self‐supervised learning ...
Yuxin Liu, Hanruo Liu
wiley   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

Exploring deep convolutional generative adversarial networks (DCGAN) in biometric systems: a survey study

Discover Artificial Intelligence
Over the past few years, there has been a proliferation of research in the area of generative adversarial networks (GANs). GANs present a novel approach to producing synthetic data in varying fields including medicine, traffic control, text transferring,
John Jenkins, Kaushik Roy
doaj   +1 more source