Results 111 to 120 of about 60,338 (274)

MTCA‐Net: Multi‐Task Cascade Analysis Network for Real‐Time Sperm Quality Analysis

Advanced Intelligent Systems, EarlyView.
This article proposes MTCA‐Net, a multi‐task cascaded analysis network for real‐time sperm quality assessment in intracytoplasmic sperm injection. The framework integrates detection, tracking, and segmentation modules to jointly analyze sperm morphology and motility.
Jiajin Li, Wenwen Sun, Jun He, Xinyu Fan, Xuecheng Ge, Fengya Lu, Yadan Wang, Yi Wang, Zhiguo Zhang, Qibing Wu, Jinhua Zhou   +10 more
wiley   +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

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

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

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

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

Application of Self-Attention Generative Adversarial Network for Electromagnetic Imaging in Half-Space

Sensors
In this paper, we introduce a novel artificial intelligence technique with an attention mechanism for half-space electromagnetic imaging. A dielectric object in half-space is illuminated by TM (transverse magnetic) waves.
Chien-Ching Chiu, Yang-Han Lee, Po-Hsiang Chen, Ying-Chen Shih, Jiang Hao   +4 more
doaj   +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

Understanding Generative Adversarial Networks (GANs): A Review

Control Systems and Optimization Letters
Generative Adversarial Networks (GANs) is an important breakthrough in artificial intelligence that uses two neural networks, a generator and a discriminator, that work in an adversarial framework. The generator generates synthetic data, while the discriminator evaluates the authenticity of the data.
Purwono Purwono, Annastasya Nabila Elsa Wulandari, Alfian Ma'arif, Wael A. Salah   +3 more
openaire   +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