Results 201 to 210 of about 124,232 (320)
Optical Neuromorphic Technology Catalyzes the Next‐Generation Mobile Communication Technology
Advancements in optical computing could revolutionize next‐generation wireless communication. The review highlights the role of photonic integrated circuits in implementing neural network operations and discusses their benefits, such as high computational density.
Xiaoxiong Song +6 more
wiley +1 more source
Anchor-controlled generative adversarial network for high-fidelity electromagnetic and structurally diverse metasurface design. [PDF]
Zeng Y, Cao H, Jin X.
europepmc +1 more source
IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition
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
Improved Face Image Super-Resolution Model Based on Generative Adversarial Network. [PDF]
Liu Q, Sun Y, Chen L, Liu L.
europepmc +1 more source
Language and Noise Transfer in Speech Enhancement Generative Adversarial Network [PDF]
Santiago Pascual +4 more
openalex +1 more source
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
Synthetic electroretinogram signal generation using a conditional generative adversarial network. [PDF]
Kulyabin M +6 more
europepmc +1 more source
ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans [PDF]
F. Din-Houn Lau +4 more
openalex +1 more source
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

