A new editorial was published in Oncotarget, Volume 16, on April 4, 2025, titled “Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques.” ...

While deepfake generation advances in complexity, it also becomes more computationally demanding. In contrast, detection is learning to do more with less.

Extending our preliminary model DO-GAN, we propose the methods to apply the double oracle framework concept to Adversarial Neural Architecture Search (NAS ... For scalability of the framework where ...

Contributions may include studies on energy-efficient neural network models for robotic systems, strategies to enhance robotic resilience in dynamic, real-world settings, or novel neural network ...

Academic references to influential breakthroughs in neural networks, transformer designs ... Most companies utilize GAN most commonly in their generative AI patents, but a lack of specificity ...

Using these datasets, 72 models with varying configurations – including different convolutional neural network architectures ... also indicating that classic and GAN-based augmentation approaches had ...

Cambridge GaN Devices’s hybrid architecture for power modules combines gallium-nitride and IGBT devices to give EV designers an efficient, affordable solution for drivetrains and accessories.

The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...