Results 191 to 200 of about 30,188 (287)

A lung CT vision foundation model facilitating disease diagnosis and medical imaging. [PDF]

Nat Commun
Gao Z, Zhang G, Liang H, Liu J, Ma L, Wang T, Guo Y, Chen Y, Yan Z, Chen X, He J, Xu F, Wong TY, Guo Y, Dai Q.   +14 more
europepmc   +1 more source

Signature Design of Sparsely Spread Code Division Multiple Access Based on Superposed Constellation Distance Analysis

, 2017
Guanghui Song, Xianbin Wang, Jun Cheng
openalex   +1 more source

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source

Modeling neuron-astrocyte interactions in neural networks using distributed simulation. [PDF]

PLoS Comput Biol
Jiang HJ, Aćimović J, Manninen T, Ahokainen I, Stapmanns J, Lehtimäki M, Diesmann M, van Albada SJ, Plesser HE, Linne ML.   +9 more
europepmc   +1 more source

Real‐time fault detection in multicomponent nuclear‐waste slurries through data fusion of spectroscopic sensors

AIChE Journal, EarlyView.
Abstract Three instruments–Raman spectroscopy, attenuated total reflectance–Fourier transform infrared spectroscopy, and focused beam reflectance measurement–were used to detect sensor faults, mixing faults, and unanticipated chemistry in a system of multicomponent slurries.
Steven H. Crouse, Ronald W. Rousseau, Martha A. Grover   +2 more
wiley   +1 more source

Continual familiarity decoding from recurrent connections in spiking networks. [PDF]

PLoS Comput Biol
Zemliak V, Pipa G, Nieters P.
europepmc   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Multimodal emotion recognition via adaptive high-order transforme network. [PDF]

PLoS One
Lu Y, Feng H.
europepmc   +1 more source

Dataset for Spatial Modulation Aided Sparse Code-Division Multiple Access

, 2017
Yusha Liu, Lie‐Liang Yang, Lajos Hanzo
openalex   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source