Results 171 to 180 of about 259,517 (255)
Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley +1 more source
A Comparative Evaluation of Meta-Learning Models for Few-Shot Chest X-Ray Disease Classification. [PDF]
Quiñonez-Baca LC +5 more
europepmc +1 more source
Large Language Model‐Based Chatbots in Higher Education
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
A meta-learning approach for selectivity prediction in asymmetric catalysis. [PDF]
Singh S, Hernández-Lobato JM.
europepmc +1 more source
In this research, a paradigm of parameter estimation method for pneumatic soft hand control is proposed. The method includes the following: 1) sampling harmonic damping waves, 2) applying pseudo‐rigid body modeling and the logarithmic decrement method, and 3) deriving position and force control.
Haiyun Zhang +4 more
wiley +1 more source
Low-carbon supply chain logistics risk prediction using meta-learning-based graph convolutional network on prototype space. [PDF]
Wang Y, Sun Y.
europepmc +1 more source
This study proposes a robust, generalizable new approach for facial type diagnosis. Based on landmark detection and pose normalization, a 94.7% diagnostic accuracy is achieved by Combined Heatmap Regression and Coordinate Regression network. This research makes the AI‐generated preliminary diagnosis more interpretable and reducing the impact of ...
Qianyang Xie +12 more
wiley +1 more source
Context-informed few-shot molecular property prediction via heterogeneous meta-learning. [PDF]
Xue J, Liu J, Chen K.
europepmc +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
MLG-STPM: Meta-Learning Guided STPM for Robust Industrial Anomaly Detection Under Label Noise. [PDF]
Huang YH, Lo SL, Chen ZQ, Wang JK.
europepmc +1 more source

