Results 131 to 140 of about 60,338 (274)

Autoencoder-based conditional optimal transport generative adversarial network for medical image generation

Visual Informatics
Medical image generation has recently garnered significant interest among researchers. However, the primary generative models, such as Generative Adversarial Networks (GANs), often encounter challenges during training, including mode collapse. To address
Jun Wang, Bohan Lei, Liya Ding, Xiaoyin Xu, Xianfeng Gu, Min Zhang   +5 more
doaj   +1 more source

A Generative Adversarial Network (GAN) Fingerprint Approach Over LTE

IEEE Access
Recent advancements in communication technologies have significantly enhanced localization techniques, improving both accuracy and operating modes. Initially, localization methods relied on global navigation satellite systems, offering high accuracy but proving inefficient in Non-Line-of-Sight scenarios.
Luigi Serreli, Mauro Fadda, Roberto Girau, Pietro Ruiu, Daniele D. Giusto, Matteo Anedda   +5 more
openaire   +3 more sources

From Data to Decisions: How Machine Learning and Generative Artificial Intelligence Are Redefining Precision Medicine in Kidney Transplantation

Organ Medicine, EarlyView.
This review evaluates how machine learning, multimodal integration, and generative AI optimize kidney transplant outcomes. These tools enable superior prediction and personalized therapy but face hurdles in data volume, generalizability, and ethics. Future clinical adoption depends on continued innovation and multidisciplinary collaboration to overcome
Maoxin Liao, Cheng Yang
wiley   +1 more source

Survey on AI‐Enabled Computer Vision Technologies and Applications for Space Robotic Missions

Journal of Field Robotics, EarlyView.
ABSTRACT This survey provides a comprehensive overview of recent advancements and challenges in Artificial Intelligence (AI)‐enabled computer vision (CV) techniques for space robotic missions, spanning critical phases such as Entry, Descent, and Landing (EDL), orbital operations, and planetary surface exploration.
Maciej Quoos, Steven Kay, Julia Wajoras, Robert Field, Evridiki V. Ntagiou, Fakher Mohammad, Yang Gao   +6 more
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Generative adversarial networks with texture recovery and physical constraints for remote sensing image dehazing

Scientific Reports
The scattering of tiny particles in the atmosphere causes a haze effect on remote sensing images captured by satellites and similar devices, significantly disrupting subsequent image recognition and classification.
Yanfei Jia, Wenshuo Yu, Liquan Zhao
doaj   +1 more source

Convergence Problems with Generative Adversarial Networks (GANs)

, 2018
47 pages, 4 ...
openaire   +2 more sources

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source

Integrating multimodal data and machine learning for entrepreneurship research

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley   +1 more source

Organizing across cognitive asymmetry in human–AI collaboration: A study of perfume creation

Strategic Management Journal, EarlyView.
Abstract Research Summary As organizations increasingly adopt generative AI (GenAI), they face a strategic challenge: not only deciding which tasks AI should perform, but also how to organize the integration of human and AI efforts to produce viable solutions.
Tomoko Yokoi, Daniella Laureiro‐Martinez, Federico Magni, Stefano Brusoni   +3 more
wiley   +1 more source