Results 51 to 60 of about 438,874 (275)

Improving part-of-speech tagging in Amharic language using deep neural network

Heliyon, 2023
To date, several POS taggers have been introduced to facilitate the success of semantic analysis for different languages. However, the task of POS tagging becomes a bit intricate in morphologically complex languages, like Amharic.
Sintayehu Hirpassa, G.S. Lehal
doaj   +1 more source

Dialogue Act Recognition via CRF-Attentive Structured Network

, 2017
Dialogue Act Recognition (DAR) is a challenging problem in dialogue interpretation, which aims to attach semantic labels to utterances and characterize the speaker's intention.
Ang Jeremy, Chen Yun-Nung, Chen Zheqian, Geertzen Jeroen, Kalchbrenner Nal, Lee Ji Young, Pan Boyuan   +6 more
core   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields

Remote Sensing, 2019
Classification of hyperspectral images is a challenging task owing to the high dimensionality of the data, limited ground truth data, collinearity of the spectra and the presence of mixed pixels.
Vera Andrejchenko, Wenzhi Liao, Wilfried Philips, Paul Scheunders   +3 more
doaj   +1 more source

Stochastic Loewner evolution in doubly connected domains [PDF]

, 2004
This paper introduces the annulus SLE$_\kappa$ processes in doubly connected domains. Annulus SLE$_6$ has the same law as stopped radial SLE$_6$, up to a time-change.
Zhan, Dapeng
core   +2 more sources

A Nano‐Interception Strategy for Chronic Heart Failure: Prussian Blue Nanoparticles Disrupt Fibroblast‐Immune Communication via CCL2 Sequestration

Advanced Materials, EarlyView.
A nano‐interception strategy disrupts pathogenic fibroblast–macrophage crosstalk in chronic heart failure. Scalable Prussian blue nanoparticles selectively sequester CCL2 via ultrahigh‐affinity binding, preventing CCR2+ macrophage recruitment and breaking a key fibro‐inflammatory circuit. This approach demonstrates robust efficacy in murine and porcine
Bo Chen, Gao Wei, Guowei Zeng, Haoyu Li, Rongrong Wu, Hongyu Yan, Zijie Zhou, Kai Luo, Xiaoyang Zhang, Cong Li, Longming Huang, Lingyan Cheng, Xinjie Zhang, Jinghao Zheng, Bozhong Shi, Xiaojun Cai, Xiaomin He   +16 more
wiley   +1 more source

TIER: Temporal Convolutional Network Information Extractor With Conditional Random Field

IEEE Access
As data scales expand, effectively modeling long-distance dependencies has become crucial for information extraction. We propose TIER, which combines the Temporal Convolutional Network (TCN) and the Conditional Random Field (CRF). The dilated convolution
Huiwen Wu, Xiubo Zhang, Tengyuan Zhou, An Hu   +3 more
doaj   +1 more source

Hierarchical Terrain Classification Based on Multilayer Bayesian Network and Conditional Random Field

Remote Sensing, 2017
This paper presents a hierarchical classification approach for Synthetic Aperture Radar (SAR) images. The Conditional Random Field (CRF) and Bayesian Network (BN) are employed to incorporate prior knowledge into this approach for facilitating SAR image ...
Chu He, Xinlong Liu, Di Feng, Bo Shi, Bin Luo, Mingsheng Liao   +5 more
doaj   +1 more source

Conditional Random Field Autoencoders for Unsupervised Structured Prediction [PDF]

, 2014
We introduce a framework for unsupervised learning of structured predictors with overlapping, global features. Each input's latent representation is predicted conditional on the observable data using a feature-rich conditional random field.
Ammar, Waleed, Dyer, Chris, Smith, Noah A.   +2 more
core   +2 more sources

Discriminative word alignment with conditional random fields [PDF]

Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06, 2006
In this paper we present a novel approach for inducing word alignments from sentence aligned data. We use a Conditional Random Field (CRF), a discriminative model, which is estimated on a small supervised training set. The CRF is conditioned on both the source and target texts, and thus allows for the use of arbitrary and overlapping features over ...
Blunsom, P, Cohn, T
openaire   +2 more sources