On‐Device Brain Tumor Classification from MR Images Using Smartphone
Advanced Intelligent Systems, EarlyView.Herein, various deep learning models are trained for brain tumor classification task, and model performances are compared. The performance is further improved by using the proposed preprocessing algorithm before training. The MobileViT model, which is the best‐performing model in terms of balance between inference time and success rate, is integrated ...
Halil Ibrahim Ustun +3 more
wiley +1 more source
IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition
Advanced Intelligent Systems, EarlyView.This study presents IAR‐Net, a deep‐learning framework for catheterization action recognition. To ensure optimality, this study quantifies interoperator similarities and differences using statistical tests, evaluates the distribution fidelity of synthetic data produced by six generative models, and benchmarks multiple deep‐learning models.
Toluwanimi Akinyemi +7 more
wiley +1 more source
Recursive Conditional Generative Adversarial Networks for Video Transformation [PDF]
, 2019 San Kim, Doug Young Suh
openalex +1 more source
A Generative Adversarial Network approach for automatic inspection in automotive assembly lines
, 2022 Joceleide Dalla Costa Mumbelli +4 more
openalex +2 more sources
Generative Adversarial Networks for students' structure prediction. Preliminary research [PDF]
, 2022 Agata Kozina +6 more
openalex +1 more source
Advanced Intelligent Systems, EarlyView.This study presents a robot‐assisted remote rehabilitation system for postoperative ankle fractures. The 2.634 kg modular system uses wireless control and deep learning to predict force delays, achieving 100 Hz control (normalized root mean square error ≤ 10.89%).
Zhiyuan He +4 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
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 +2 more
wiley +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 +5 more
wiley +1 more source
Restoration of Marker Occluded Hematoxylin and Eosin Stained Whole Slide Histology Images Using Generative Adversarial Networks [PDF]
, 2020 Bairavi Venkatesh +3 more
openalex +1 more source