Results 1 to 10 of about 240,407 (142)

Knowledge Representation for Multi-Scale Physiology Route Modeling [PDF]

Frontiers in Neuroinformatics, 2021
We present a framework for the topological and semantic assembly of multiscale physiology route maps. The framework, called ApiNATOMY, consists of a knowledge representation (KR) model and a set of knowledge management (KM) tools. Using examples of ApiNATOMY route maps, we present a KR format that is suitable for the analysis and visualization by KM ...
Kokash N., De Bono B.
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Conformal-Based Surface Morphing and Multi-Scale Representation [PDF]

Axioms, 2014
This paper presents two algorithms, based on conformal geometry, for the multi-scale representations of geometric shapes and surface morphing. A multi-scale surface representation aims to describe a 3D shape at different levels of geometric detail, which allows analyzing or editing surfaces at the global or local scales effectively.
Lam, Ka, Wen, Chengfeng, Lui, Lok
openaire   +4 more sources

A multi-granularity feature fusion approach with attention for facial expression recognition [PDF]

Scientific Reports
Facial expression recognition (FER) has been challenged by insufficient sensitivity to fine-grained local variations and limited feature representation capabilities in existing methods. To address these issues, we propose a novel FER method MGFA based on
Guo Yu
doaj   +2 more sources

M³-TransUNet: Medical Image Segmentation Based on Spatial Prior Attention and Multi-Scale Gating [PDF]

Journal of Imaging
Medical image segmentation presents substantial challenges arising from the diverse scales and morphological complexities of target anatomical structures.
Zhigao Zeng, Jiale Xiao, Shengqiu Yi, Qiang Liu, Yanhui Zhu   +4 more
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Multi-Scale Graphical Representation of Cell Environment

2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
We present a multi-scale graphical network that can capture the relevant representations of individual cell morphology, topological structure of cell communities in a tissue image, as well as whole slide level attributes. This helps to effectively merge the disease relevant cell morphology to the overall topological context within the sample, within ...
Theissen, H, Chakraborty, T, Malacrino, S, Royston, D, Rittscher, J   +4 more
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Chinese Sentiment Analysis Based on CNN-BiLSTM Model of Multi-level and Multi-scale Feature Extraction [PDF]

Jisuanji kexue, 2023
Sentiment analysis,as a sub-field of natural language processing(NLP),plays a very important role in public opinion monitoring.In the Chinese sentiment analysis task,the existing methods only consider sentiment features from single-level and single-scale,
WANG Lin, MENG Zuqiang, YANG Lina
doaj   +1 more source

Toward Efficient Object Detection in Aerial Images Using Extreme Scale Metric Learning

IEEE Access, 2021
In aerial image object detection, how to efficiently detect different size objects in input images of different scales and obtain a unified multi-scale representation of the object is an important issue.
Ren Jin, Junning Lv, Bin Li, Jianchuan Ye, Defu Lin   +4 more
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A scale‐sensitive heatmap representation for multi‐person pose estimation

IET Image Processing, 2022
Multi‐person pose estimation is a challenging vision task that can be seriously affected by keypoint scale variation. Existing heatmap‐based approaches are devoted to reducing the effect by optimizing backbone architecture or loss functions, but the ...
Congju Du, Han Yu, Li Yu
doaj   +1 more source

GENERAL ANALYZING AND RESEARCH ON UNCERTAINTY OF MULTI-SCALE REPRESENTATION FOR STREET-BLOCK SETTLEMENT [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013
Analyzing and evaluating the reliability of multi-scale representation of spatial data are already becoming an important issue of the current digital cartography and GIS. Settlement place is the main content of maps.
F. Xu, J. Niu, Z. Chi, W. Xie
doaj   +1 more source

Learning Multi-Scale Representations for Material Classification [PDF]

, 2014
The recent progress in sparse coding and deep learning has made unsupervised feature learning methods a strong competitor to hand-crafted descriptors. In computer vision, success stories of learned features have been predominantly reported for object recognition tasks.
Li, W., Fritz, M.
openaire   +5 more sources