Results 291 to 300 of about 2,841,987 (371)

Comparative analysis of optimized logistic regression with state-of-the-art models for complex gastroenterological image analysis. [PDF]

Front Med (Lausanne)
Cristea DM, Sima I, Iantovics LB.
europepmc   +1 more source

Fourier descriptors for shape characterization

, 2011
Olena Buchko
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Low-Rank Representation and Data Compression of Full-Field Displacement Maps for Structural Modal Analysis and Damage Identification. [PDF]

Sensors (Basel)
Li Y, Huang Y, Li Z, Yin Z, Cao S.
europepmc   +1 more source

Using Shape Descriptors in Shape Data Classification

Journal of Statistical Sciences
openaire   +1 more source

Rotation Invariant Local Shape Descriptors for Classification of Archaeological 3D Models

, 2016
Roman Rangel, Edgar Francisco, Jimenez-Badillo, Diego, Marchand-Maillet, Stéphane   +2 more
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3D deep shape descriptor

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
Shape descriptor is a concise yet informative representation that provides a 3D object with an identification as a member of some category. We have developed a concise deep shape descriptor to address challenging issues from ever-growing 3D datasets in areas as diverse as engineering, medicine, and biology.
Yi Fang, null Jin Xie, null Guoxian Dai, null Meng Wang, null Fan Zhu, null Tiantian Xu, Edward Wong   +6 more
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DeepShape: Deep-Learned Shape Descriptor for 3D Shape Retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
Complex geometric variations of 3D models usually pose great challenges in 3D shape matching and retrieval. In this paper, we propose a novel 3D shape feature learning method to extract high-level shape features that are insensitive to geometric deformations of shapes.
, Jin Xie, , Guoxian Dai, , Fan Zhu, Edward K, Wong, , Yi Fang   +4 more
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Deformable HOG-Based Shape Descriptor

2013 12th International Conference on Document Analysis and Recognition, 2013
In this paper we deal with the problem of recognizing handwritten shapes. We present a new deformable feature extraction method that adapts to the shape to be described, dealing in this way with the variability introduced in the handwriting domain. It consists in a selection of the regions that best define the shape to be described, followed by the ...
Jon Almazan, Alicia Fornes, Ernest Valveny   +2 more
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A Learning Robust and Discriminative Shape Descriptor for Plant Species Identification

IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2022
Plant identification based on leaf images is a widely concerned application field in artificial intelligence and botany. The key problem is extracting robust discriminative features from leaf images and assigning a measure of similarity.
Chengzhuan Yang, L. Fang, Qian Yu, Hui Wei   +3 more
semanticscholar   +1 more source

SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification

European Conference on Computer Vision, 2020
Point clouds are often the default choice for many applications as they exhibit more flexibility and efficiency than volumetric data. Nevertheless, their unorganized nature -- points are stored in an unordered way -- makes them less suited to be ...
Yida Wang, D. Tan, N. Navab, Federico Tombari   +3 more
semanticscholar   +1 more source