Results 181 to 190 of about 221,929 (334)

A Generative Adversarial Network approach for automatic inspection in automotive assembly lines

, 2022
Joceleide Dalla Costa Mumbelli, Giovanni A. Guarneri, Yuri Kaszubowski Lopes, Dalcimar Casanova, Marcelo Teixeira   +4 more
openalex   +2 more sources

Loss‐Based Ensemble Generative Adversarial Network Model for Enhancing the Sperm Morphology Classification

Advanced Intelligent Systems, EarlyView.
A loss‐based ensemble generative adversarial network (GAN) framework is proposed to address mode collapse in sperm morphology classification. By integrating spatial augmentation and multiple GAN models, the study enhances synthetic data quality. The Shifted Window Transformer achieves 95.37% accuracy on the HuSHeM dataset, outperforming previous ...
Berke Cansiz, Hamza Osman Ilhan, Gorkem Serbes   +2 more
wiley   +1 more source

Generative Adversarial Networks for students' structure prediction. Preliminary research [PDF]

, 2022
Agata Kozina, Zdzisław Kes, Marcin Hernes, Paweł Golec, Krzysztof Nowosielski, Olena Sidor, Korlan Zhanat   +6 more
openalex   +1 more source

Robotic Needle Steering for Percutaneous Interventions: Sensing, Modeling, and Control

Advanced Intelligent Systems, EarlyView.
This review examines recent advances in robotic needle steering for percutaneous interventions, highlighting closed‐loop sensing, physics‐informed tissue‐needle interaction modeling, and real‐time trajectory planning and control. It synthesizes innovations in deep learning, fiber‐optic feedback, and adaptive control strategies, and outlines emerging ...
Fangjiao Zhao, Ruixue Xu, Wujun Zhao, Xi‐Ming Sun, Yu Sun, Changsheng Dai   +5 more
wiley   +1 more source

Flexible Android Malware Detection Model based on Generative Adversarial Networks with Code Tensor [PDF]

, 2022
Yang Zhao, Fengyang Deng, Linxi Han
openalex   +1 more source

BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models

Advanced Intelligent Systems, EarlyView.
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan, Kang Fu, Sijing Wu, Yunhao Li, Zicheng Zhang, Qiang Hu, Xiongkuo Min, Guangtao Zhai   +7 more
wiley   +1 more source

Multitarget Recognition of Flower Images Based on Lightweight Deep Neural Network and Transfer Learning

Advanced Intelligent Systems, EarlyView.
This article proposes a lightweight YOLOv4‐based detection model using MobileNetV3 or CSPDarknet53_tiny, achieving 30+ FPS and higher mAP. It also presents a ShuffleNet‐based classification model with transfer learning and GAN‐augmented images, improving generalization and accuracy.
Qingyang Liu, Yanrong Hu, Hongjiu Liu
wiley   +1 more source

Restoration of Marker Occluded Hematoxylin and Eosin Stained Whole Slide Histology Images Using Generative Adversarial Networks [PDF]

, 2020
Bairavi Venkatesh, Tosha Shah, Antong Chen, Soheil Ghafurian   +3 more
openalex   +1 more source

Generative Adversarial Framework to Calibrate Excursion Set Models for the 3D Morphology of All‐Solid‐State Battery Cathodes

Advanced Intelligent Systems, EarlyView.
Worklow for calibrating excursion sets of random fields using methods from generative artificial intelligence. This article presents a computational method for generating virtual 3D morphologies of functional materials using low‐parametric stochastic geometry models, that is, digital twins, calibrated with 2D microscopy images.
Orkun Furat, Sabrina Weber, Anina Dufter, Johannes Schubert, René Rekers, Maximilian Luczak, Erik Glatt, Andreas Wiegmann, Jürgen Janek, Anja Bielefeld, Volker Schmidt   +10 more
wiley   +1 more source

Securing Generative Artificial Intelligence with Parallel Magnetic Tunnel Junction True Randomness

Advanced Intelligent Systems, EarlyView.
True random numbers can protect generative artificial intelligence (GAI) models from attacks. A highly parallel, spin‐transfer torque magnetic tunnel junction‐based system is demonstrated that generates high‐quality, energy‐efficient random numbers.
Youwei Bao, Shuhan Yang, Hyunsoo Yang
wiley   +1 more source