Results 61 to 70 of about 3,700 (260)
Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source
A Fast Learning Method for Multilayer Perceptrons in Automatic Speech Recognition Systems
We propose a fast learning method for multilayer perceptrons (MLPs) on large vocabulary continuous speech recognition (LVCSR) tasks. A preadjusting strategy based on separation of training data and dynamic learning-rate with a cosine function is used to ...
Chenghao Cai +3 more
doaj +1 more source
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan +8 more
wiley +1 more source
Achieving High‐Density and Stress‐Resilient Maize Breeding Via Germplasm Innovation
Global population growth and climate change have exacerbated the global food crisis. This perspective presents a conceptual framework focusing on enhancing population advantages. Several novel breeding objectives are proposed to improve density tolerance and stress resistance for yield improvement.
Xinlong Li +9 more
wiley +1 more source
Efficient Implementation of Multilayer Perceptrons: Reducing Execution Time and Memory Consumption
A technique is presented that reduces the required memory of neural networks through improving weight storage. In contrast to traditional methods, which have an exponential memory overhead with the increase in network size, the proposed method stores ...
Francisco Cedron +4 more
doaj +1 more source
We present an organic–inorganic heterostructure transistor array for neuromorphic computing, achieving 95.6% MNIST accuracy and 1.2 fJ per operation, with dynamic spatiotemporal encoding and precise vehicle direction detection under combined optical and electrical stimulation.
Wen‐Min Zhong +13 more
wiley +1 more source
Design proposal for internal seepage control structures in earth dams using multilayer perceptrons [PDF]
This paper proposes a methodology for designing internal seepage control structures in earth dams, known as wraparound systems, using Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs).
Ana Cinthya Mariano de Sousa +1 more
doaj +2 more sources
Inspired by Nostoc, a crack‐based one‐dimensional microspheres array (COMA) sensor is developed, which stabilizes crack geometry under isotropic expansion, enabling a predictable, monotonic thermal response from which true strain can be accurately extracted. The COMA sensor exhibits high sensitivity at ultralow deformation (gauge factor up to 89) and a
Wanqing Xu +7 more
wiley +1 more source
Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen +6 more
wiley +1 more source

