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Fusing Uncertain Structured Spatial Information [chapter]

Florence Dupin de Saint-Cyr, Robert Jeansoulin, Henri Prade
2008 Lecture Notes in Computer Science  
Spatial information associates properties to labeled areas. Space is partitioned into (elementary) parcels, and union of parcels constitute areas.  ...  In fusion problems, information coming from distinct sources may be expressed in terms of different conceptual and/or spatial ontologies, and may be pervaded with uncertainty.  ...  Spatial information may involve a mix of numeric and symbolic attributes, using different vocabularies more or less structured, but rarely unstructured.  ... 
doi:10.1007/978-3-540-87993-0_15 fatcat:2tygkgbtzvdxto73kkxmappalq

Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting [article]

Yue Zhang, Chengtao Peng, Liying Peng, Huimin Huang, Ruofeng Tong, Lanfen Lin, Jingsong Li, Yen-Wei Chen, Qingqing Chen, Hongjie Hu, Zhiyi Peng
2021 arXiv   pre-print
In this work, we propose a novel LiTS method to adequately aggregate multi-phase information and refine uncertain region segmentation.  ...  To this end, we introduce a spatial aggregation module (SAM), which encourages per-pixel interactions between different phases, to make full use of cross-phase information.  ...  It is seen that adding multi-phase information donates a performance boost of +6.46% in DPC; employing SAM modules to fuse features improves the performance by +3.79% in DPC; refining uncertain regions  ... 
arXiv:2108.00911v2 fatcat:kbiklrj7ebdzvm6bjk4dy5avt4

Finer Classification of Crops by Fusing UAV Images and Sentinel-2A Data

Licheng Zhao, Yun Shi, Bin Liu, Ciara Hovis, Yulin Duan, Zhongchao Shi
2019 Remote Sensing  
Accurate crop distribution maps provide important information for crop censuses, yield monitoring and agricultural insurance assessments.  ...  In addition, we test the effect of UAV image choice by fusing Sentinel-2A with different UAV images at multiples spatial resolutions: 0.03 m, 0.10 m, 0.50 m, 1.00 m and 3.00 m.  ...  We made a test to classify the crops with 0.10 m fused image using Random Forest, Support Vector Machine and Neural Net.  ... 
doi:10.3390/rs11243012 fatcat:y4gsh5qzejckda45kisomarc4e

Hierarchical Disentangling Network for Building Extraction from Very High Resolution Optical Remote Sensing Imagery

Jianhao Li, Yin Zhuang, Shan Dong, Peng Gao, Hao Dong, He Chen, Liang Chen, Lianlin Li
2022 Remote Sensing  
Additionally, with the spatial resolution of images increasing, there are diverse interior details and redundant context information present in building and background areas.  ...  However, buildings in different environments exhibit various scales, complicated spatial distributions, and different imaging conditions.  ...  Informed Consent Statement: Not applicable. Data Availability Statement: The datasets presented in this study are openly available in References [5, 6] .  ... 
doi:10.3390/rs14071767 fatcat:muyvrddcf5eknp4msoivlldbui

Understanding uncertain information in vocal description for creating virtual spatial maps

H. M. Ravindu T. Bandara, M. A. Viraj J. Muthugala, A. G. Buddhika P. Jayasekara, D. P. Chandima
2019 Paladyn: Journal of Behavioral Robotics  
", "close"to describe about spatial information.  ...  The Virtual Spatial Data Identifier (VSDI) and Uncertain Term Identifier (UTI) modules have been introduced in order to evaluate the spatial information in description to create a virtual map.  ...  The problem of fusing information contained in natural language descriptions with the robot's onboard sensors to construct spatial-semantic representations useful for in-teracting with humans has been  ... 
doi:10.1515/pjbr-2019-0032 fatcat:gmg3jbnrvfapllkcdplgmorteu

Perception enhancement using importance-driven hybrid rendering for augmented reality based endoscopic surgical navigation

Yakui Chu, Xu Li, Xilin Yang, Danni Ai, Yong Huang, Hong Song, Yurong Jiang, Yongtian Wang, Xiaohong Chen, Jian Yang
2018 Biomedical Optics Express  
First, the volume structures are enhanced using gradient-based shading to reduce the color information in low-priority regions and improve the distinctions between complicated structures.  ...  Misleading depth perception may greatly affect the correct identification of complex structures in image-guided surgery.  ...  By combining the pixels of the endoscopic image with the hybrid rendering scene, we can highlight the spatial information and remove redundant structures.  ... 
doi:10.1364/boe.9.005205 pmid:30460123 pmcid:PMC6238941 fatcat:biiirgubvzgzhpjuhtiqn5weoy

How to manage natural risks in mountain areas in a context of imperfect information? New frameworks and paradigms for expert assessments and decision-making

Jean-Marc Tacnet, Jean Dezert, Corinne Curt, Mireille Batton-Hubert, Eric Chojnacki
2014 Environment Systems and Decisions  
Tracing the information and propagating information quality from data acquisition to decisions are therefore important steps in the decision-making process.  ...  Risk management decisions are therefore based on imperfect information.  ...  Decision support tools are needed to take into account both their structural state and Fig. 28 CLPA spatial zones including quality information (Tacnet et al. 2013 ) Fig. 27 Traceability of the expert  ... 
doi:10.1007/s10669-014-9501-x fatcat:qjs5gzxkgrgw5ne5xa7oytd67a

Intrinsic image decomposition-based grey and pseudo-color medical image fusion

Jiao Du, Weisheng Li, Heliang Tan
2019 IEEE Access  
As for the image fusion rule, the defined importance of image coefficients is used to combine the decomposed two-scale components to produce the final fused image, which could keep more spatial resolution  ...  Algorithm 1 could extract structural information while reducing the noise from the MRI image. Algorithm 2 is for averaging the color information from the PET image.  ...  On the other side, the smaller σ means the more spatial detail information of the structural information. The scale factor is used to balance structural information and white matter.  ... 
doi:10.1109/access.2019.2900483 fatcat:cjq6oazrmzbxpd5xxbmryeup5u

Satellite image fusion using fuzzy logic

Suda Kumaraswamy, Dammavalam Srinivasa Rao, Nuthanapati Naveen Kumar
2016 Acta Universitatis Sapientiae: Informatica  
Conventional fusion methods are having some side effects like assertive spatial information and uncertain color information is an usually the problem in PCA and wavelet transform based fusion is a computationally  ...  images obtained from different sensors to enhance both spectral and spatial information.  ...  image and IBF is the mutual information between PAN image and fused image.  ... 
doi:10.1515/ausi-2016-0011 fatcat:z74nkp2cw5h5rm6xag2n56mpoe

Performance assessment of neuro fuzzy based image fusion of satellite images

Ch. Ramesh Babu, D. Srinivasa Rao, T. Ravi, G. Gopi
2018 International Journal of Advanced Technology and Engineering Exploration  
structures.  ...  IQI value should be high for better fused image indicates that quality of fused image is improved through fused image. 7.2Mutual information measure Mutual information measure (MIM) delivers the quantity  ... 
doi:10.19101/ijatee.2018.539005 fatcat:kwyymzqhdrd3xhltlavqzroyri

VTG-Net: A CNN Based Vessel Topology Graph Network for Retinal Artery/Vein Classification

Suraj Mishra, Ya Xing Wang, Chuan Chuan Wei, Danny Z. Chen, X. Sharon Hu
2021 Frontiers in Medicine  
The final predication is attained by fusing the CNN and GCN outputs.  ...  In this paper, we propose a new CNN based framework, VTG-Net (vessel topology graph network), for retinal A/V classification by incorporating vessel topology information.  ...  Each filter extracts information from a fixed size spatial input neighborhood [the receptive field (14) ] and propagates it to the output.  ... 
doi:10.3389/fmed.2021.750396 fatcat:lamylmtfabbxzgkwin47yiiblu

Spatial-temporal business partnership selection in uncertain environments

António Arrais-Castro, Maria Varela, Rita Ribeiro, Goran Putnik
2015 FME Transaction  
Further, SMEs are finding it increasingly difficult to include all required competences in their internal structures; therefore, they need to rely on reliable business and supplier partnerships to be successful  ...  Contemporary business models need to account for spatial-temporal changeable environments, where lack of confidence and uncertainty in data are a reality.  ...  Hence, in this paper we discuss how to tackle spatial-temporal decision making in uncertain environments.  ... 
doi:10.5937/fmet1504353a fatcat:uow56jkamrcvbcptokyn5ruxru

A Review:Image Fusion Techniques for Multisensor Images

S.A.Pan war, Sayali Malwadkar
2015 International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering  
advanced sensor technology.To avoid the limitations of single sensor images, multisensory image fusion provides the data that is suitable for further applications by eliminating the problem of lack of information  ...  Moreover, it reduces the redundancy and uncertain information. The pre-processing steps of image fusion are shown in Fig.1 .  ...  Spatial information in multi sensor images is represented by the fuzzy sets. When the membership functions and the fusion rules are applied properly a good quality fused image can be obtained.  ... 
doi:10.15662/ijareeie.2015.0401049 fatcat:gdgbonmbvnevdjeenkzbyb3mia

A Survey on Image Fusion Requirements, Techniques, Evaluation Metrics, and Its Applications

M N. Narsaiah, S Vathsal, D Venkat Reddy
2018 International Journal of Engineering & Technology  
In image fusion the images are fused at different levels of images like pixel, feature and decision level.  ...  Fusion refers to combining two or more distinct things, the main objective of employing fusion is to generate results that provides the most detailed, reliable and accurate information possible.  ...  And also decreases uncertain information and reduce repeated information.  ... 
doi:10.14419/ijet.v7i2.20.14774 fatcat:3qtwgi6psba7jgachm4gip2qee


T. Jiang, X. J. Wang
2020 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The spectral and spatial features of hyperspectral images are fully exploited, thus getting state-of-the-art classification accuracy and generalization performance.  ...  Since features fusion model inherits the structural characteristics of 1D-CNN and 2DCNN, the complementary advantages between the models are achieved.  ...  In this paper, 1D-CNN and 2D-CNN are used as feature extractors to extract spectral and spatial features respectively, and then, spectral and spatial features were fused for classification.  ... 
doi:10.5194/isprs-archives-xlii-3-w10-335-2020 fatcat:jwjnknr46ffuxfjbwv5wsrzf7m
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