Results 71 to 80 of about 438,874 (275)
IEEE Access, 2019 Accurate segmentation of brain tumor is an indispensable component for cancer diagnosis and treatment. In this paper, we propose a novel brain tumor segmentation method based on multi-cascaded convolutional neural network (MCCNN) and fully connected ...
Kai Hu +7 more
doaj +1 more source
IEEE Access, 2020 Airborne hyperspectral data have both high spectral and spatial resolutions. Although the finer spatial resolution allows more abundant spatial characteristics to be exhibited, the spectral variability problem remains. However, few of the current spatial-
Shaoyu Wang +4 more
doaj +1 more source
KGNER: Improving Chinese Named Entity Recognition by BERT Infused with the Knowledge Graph
Applied Sciences, 2022 Recently, the lexicon method has been proven to be effective for named entity recognition (NER). However, most existing lexicon-based methods cannot fully utilize common-sense knowledge in the knowledge graph.
Weiwei Hu +4 more
doaj +1 more source
Conditional Random Fields as Recurrent Neural Networks [PDF]
2015 IEEE International Conference on Computer Vision (ICCV), 2015 Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding. Recent approaches have attempted to harness the capabilities of deep learning techniques for image recognition to tackle pixel-level labelling tasks.
Zheng, S +7 more
openaire +2 more sources
ELABELA Targets Mitochondria to Modulate Heart Development
Advanced Science, EarlyView.The role of peptide ELABELA (ELA) in cardiomyocyte apoptosis and congenital heart disease (CHD) is unclear. ELA deficiency caused cardiomyocyte apoptosis and CHD. A novel ELA‐APJ‐AKT‐BCL2/BAX axis in regulating mitochondrial function and contributing to CHD pathogenesis was established.
Jian Wang +22 more
wiley +1 more source
IEEE Access, 2018 Deep convolutional neural networks (DCNNs) have been driving significant advances in semantic image segmentation due to their powerful feature representation for recognition.
Liang Zhang +7 more
doaj +1 more source
Efficient combination graph model based on conditional random field for online multi-object tracking
Complex & Intelligent Systems, 2022 The joint detection and re-identification (re-ID) strategy shares network features of detection and re-ID, sacrifices the complex probability graph model pairing strategy, and consolidates a two-stage video tracking process into a one-stage, making the ...
Junwen Zhang +3 more
doaj +1 more source
On ANOVA decompositions of kernels and Gaussian random field paths [PDF]
, 2014 The FANOVA (or "Sobol'-Hoeffding") decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis.
Durrande, Nicolas +4 more
core +2 more sources
Composition of conditional random fields for transfer learning [PDF]
Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05, 2005 Many learning tasks have subtasks for which much training data exists. Therefore, we want to transfer learning from the old, general-purpose subtask to a more specific new task, for which there is often less data. While work in transfer learning often considers how the old task should affect learning on the new task, in this paper we show that it helps
Sutton, Charles, McCallum, Andrew
openaire +3 more sources
LMO7 Suppresses Tumor‐Associated Macrophage Phagocytosis of Tumor Cells Through Degradation of LRP1
Advanced Science, EarlyView.LMO7 in tumor‐associated macrophages suppresses phagocytosis of tumor cells and limits cytotoxic T lymphocytes infiltration, fostering tumor progression. Mechanistically, LMO7 mediates the ubiquitination and degradation of the phagocytic receptor LRP1, impairing its ability to engulf tumor cells and driving macrophages toward an antitumor phenotype ...
Mengkai Li +12 more
wiley +1 more source