Results 111 to 120 of about 45,910 (264)

Spectrum of Advancements and Developments in Multidisciplinary Domains for Generative Adversarial Networks (GANs). [PDF]

Arch Comput Methods Eng, 2021
Rizvi SKJ, Azad MA, Fraz MM.
europepmc   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source

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

Generative Adversarial Networks (GANs) For Data Augmentation

International Journal of Latest Technology in Engineering Management & Applied Science
Abstract: Generative Adversarial Network is powerful tools for creating new and realistic data to help in to improve machine learning models, specifically when there’s not enough labeled data. It has two parts: Generator-which create a fake data and Discriminator-which tries to tell real data from fake.
null Komal Korade, null Sharayu Naiknavare   +1 more
openaire   +1 more source

Real‐time monitoring of tunnel structures using digital twin and artificial intelligence: A short overview

Deep Underground Science and Engineering, EarlyView.
How artificial intelligence (AI) and digital twin (DT) technologies are revolutionizing tunnel surveillance, offering proactive maintenance strategies and enhanced safety protocols. It explores AI's analytical power and DT's virtual replicas of infrastructure, emphasizing their role in optimizing maintenance and safety in tunnel management.
Mohammad Afrazi, Danial Jahed Armaghani, Hossein Afrazi, Hadi Fattahi, Pijush Samui   +4 more
wiley   +1 more source

Do generative models learn rare generative factors?

Frontiers in Artificial Intelligence
Generative models are becoming a promising tool in AI alongside discriminative learning. Several models have been proposed to learn in an unsupervised fashion the corresponding generative factors, namely the latent variables critical for capturing the ...
Fasih Haider, Edward Moroshko, Yuyang Xue, Sotirios A. Tsaftaris   +3 more
doaj   +1 more source

MR-GAN: Manifold Regularized Generative Adversarial Networks

, 2018
arXiv admin note: text overlap with arXiv:1706.04156 by other ...
Li, Qunwei, Kailkhura, Bhavya, Anirudh, Rushil, Zhou, Yi, Liang, Yingbin, Varshney, Pramod   +5 more
openaire   +2 more sources

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

Application of GAN–CNN in Risk Assessment of Pipeline Failures in Multiphase Pipeline With Image Information Encoding Approach

Energy Science &Engineering, EarlyView.
Field data from multiphase pipelines are transformed into grayscale images via Image Information Encoding, preserving feature values and interparameter relationships. A GAN–CNN model generates synthetic images that are decoded to expand the original database.
Sihang Chen, Na Zhang, Biyuan Shui
wiley   +1 more source

Evaluating the impact of generative adversarial models on the performance of anomaly intrusion detection

IET Networks
With the increasing rate and types of cyber attacks against information systems and communication infrastructures, many tools are needed to detect and mitigate against such attacks, for example, Intrusion Detection Systems (IDSs).
Mohammad Arafah, Iain Phillips, Asma Adnane   +2 more
doaj   +1 more source