13.3.12 Basic Comparison of Relational Network Descriptions

Tversky, A.,
Features of Similarity,
PsychR(84), No. 4, July 1977, pp. 327-352. Feature Contrast model. Relevant to database queries. BibRef 7707

Price, K.E., and Reddy, R.,
Matching Segments of Images,
PAMI(1), No. 1, January 1979, pp. 110-116. BibRef 7901
Earlier:
Symbolic Image Registration and Change Detection,
DARPA77(28-31). Matching, Regions. Change Detection. The original matching paper of this sequence. Image to image matching. Using graph descriptions where nodes have descriptions (size, location, color, shape, texture, etc.) and links to other nodes using relations (above, below, adjacent, inside, etc.) BibRef

Price, K.E.[Keith E.], Reddy, R.,
Change Detection and Analysis in Multi-Spectral Images,
IJCAI77(619-625). BibRef 7700
Earlier: A1 Only: CMU-CS-TRDecember 1976. BibRef Ph.D.Thesis, CS. Change Detection. Change detection, at the symbolic level applied to aerial images, color ground level images, and SAR. BibRef

Nevatia, R., and Price, K.E.,
Locating Structures in Aerial Images,
PAMI(4), No. 5, September 1982, pp. 476-484. BibRef 8209 USC Computer Vision BibRef
Earlier: ICPR78(686-690). Matching, Lines. The matching procedure assumes that regions are extracted and property values such as size, average intensity, position, and shape parameters are computed. Additionally, relations between regions such as relative position, adjacency, closeness, etc. are computed. This description is given in the form of a semantic network where regions are nodes and relations are the links. These systems find the matching regions one at a time (without backtracking), with the order either determined by the user or by sorting on some feature (e.g. largest first). Features and relations are given three different weights (strong, average and weak) that determines their contribution to the match rating function. BibRef

Rosenfeld, A.,
Distances Between Fuzzy Sets,
PRL(3), 1985, pp. 229-233. Fuzzy Sets. BibRef 8500

Chaudhuri, B.B., Rosenfeld, A.,
On a Metric Distance Between Fuzzy-Sets,
PRL(17), No. 11, September 16 1996, pp. 1157-1160. 9611
BibRef

Sanfeliu, A.,
Syntactic and Structural Methods in Document Image Analysis,
SDIA92(xx-yy). 0905
BibRef
Earlier:
Structural Similarity Measures for Classifying 2D and 3D Partially Hidden, Occluded and Deformed Objects,
ICPR86(1294-1296).
See also TC2: Structural and Syntactic Pattern-Recognition: Aims, Scope, History and Activities. BibRef

Feustel, C.D., Shapiro, L.G.,
The Nearest Neighbor Problem in an Abstract Metric Space,
PRL(1), No. 2, 1982, 125-128. BibRef 8200

Shapiro, L.G., and Haralick, R.M.,
A Metric for Comparing Relational Descriptions,
PAMI(7), No. 1, January 1985, pp. 90-94. Distance Metric. The paper discusses a technique for generating a metric which compares two relational structures. Some background is given, but it does not mention some that are in use in real programs. Structural_Error = (Relations in Image A not in Image B) + (Relations in Image B not in Image A). BibRef 8501

Shapiro, L.G.,
Relational Matching,
HPRIP-CV94(475-496). BibRef 9400
Earlier: With: Haralick, R.M., AppOpt(26), No. 10, May 15, 1987, pp. 1845-1851. Survey, Matching. Matching, Survey. A survey (overview) of relational matching with only their references. BibRef

Shapiro, L.G., and Haralick, R.M.,
Organization of Relational Models for Scene Analysis,
PAMI(4), No. 6, November 1982, pp. 595-602. An earlier 2-D version is under the 2-D analysis chapter. A large data base can be organized by using a simple relational distance metric, followed by either clustering by similar values of the metric or a binary decision tree arrangement. BibRef 8211

Haralick, R.M., Camps, O.I.[Octavia I.], Shapiro, L.G., and
A Probabilistic Matching Algorithm for Computer Vision,
AMAI(10), 1994, pp. 85-124. BibRef 9400

Shapiro, L.G., and Lu, H.,
Accumulator-Based Inexact Matching Using Relational Summaries,
MVA(3), No. 3, 1990, pp. 143-158. BibRef 9000

Shapiro, L.G.,
The Use of Numerical Relational Distance and Symbolic Differences for Organizing Models and for Matching,
T3DMP86(255-270). BibRef 8600
Earlier:
Using Symbolic Differences to Organize Relational Models,
CVPR839377-379). BibRef

Boninsegna, M., Rossi, M.,
Similarity Measures In Computer Vision,
PRL(15), No. 12, December 1994, pp. 1255-1260. BibRef 9412

Oflazer, K.,
Error Tolerant Retrieval of Trees,
PAMI(19), No. 12, December 1997, pp. 1376-1380.
IEEE DOI 9712
Actually matching of trees to find the closest one. Used in machine translation, NL work. BibRef

Tanaka, E., Takemasa, K., Masuda, S.,
A Distance Measure for Molecular Structures and Its Computing Method,
PRL(19), No. 3-4, March 1998, pp. 373-381. 9807
BibRef

Sim, D.G.[Dong-Gyu], Kwon, O.K.[Oh-Kyu], Park, R.H.[Rae-Hong],
Object Matching Algorithms Using Robust Hausdorff Distance Measures,
IP(8), No. 3, March 1999, pp. 425-429.
IEEE DOI BibRef 9903
Earlier: A2, A1, A3:
New Hausdorff distances based on robust statistics for comparing images,
ICIP96(III: 21-24).
IEEE DOI 9610
BibRef

Kwon, O.K.[Oh-Kyu], Sim, D.G.[Dong-Gyu], Park, R.H.[Rae-Hong],
Robust Hausdorff distance matching algorithms using pyramidal structures,
PR(34), No. 10, October 2001, pp. 2005-2013.
Elsevier DOI 0108
BibRef
Earlier:
Pyramidal Robust Hausdorff Distance for Object Matching,
ICIP99(IV:88-92).
IEEE DOI BibRef

Kwon, O.K.[Oh-Kyu], Kim, D.S.[Dong-Soo], Suh, J.W.[Jung Wook],
Accurate M-hausdorff distance similarity combining distance orientation for matching multi-modal sensor images,
PRL(32), No. 7, 1 May 2011, pp. 903-909.
Elsevier DOI 1101
M-Hausdorff distance; Distance orientation map; Multi-modal image alignment BibRef

Foggia, P., Sansone, C., Tortorella, F., Vento, M.,
Definition and Validation of a Distance Measure Between Structural Primitives,
PAA(2), No. 3, 1999, pp. 215-227. BibRef 9900

de Stefano, C., Foggia, P., Tortorella, F., Vento, M.,
A Distance Measure for Structural Descriptions Using Circular Arcs as Primitives,
ICPR96(II: 290-294).
IEEE DOI 9608
(Univ. di Napoli FedericoII, I) BibRef

Bunke, H., Jiang, X., and Kandel, A.,
On the Minimum Common Supergraph of Two Graphs,
Computing(65), No. 1, 2000, pp. 13-25. BibRef 0001

Bunke, H., Guidobaldi, C., Vento, M.,
Weighted minimum common supergraph for cluster representation,
ICIP03(II: 25-28).
IEEE DOI 0312
BibRef

Wang, J.T.L.[Jason T.L.], Zhang, K.Z.[Kai-Zhong],
Finding Similar Consensus Between Trees: An Algorithm and a Distance Hierarchy,
PR(34), No. 1, January 2001, pp. 127-137.
Elsevier DOI 0010
BibRef

Wallis, W.D., Shoubridge, P., Kraetz, M., Ray, D.,
Graph distances using graph union,
PRL(22), No. 6-7, May 2001, pp. 701-704.
Elsevier DOI 0105
BibRef

Miller, M.I., Younes, L.,
Group Actions, Homeomorphisms, and Matching: A General Framework,
IJCV(41), No. 1-2, January-February 2001, pp. 61-84.
DOI Link Metrics on images for matching. 0105
BibRef

Jiang, X.Y.[Xiao-Yi], Münger, A.[Andreas], Bunke, H.[Horst],
On Median Graphs: Properties, Algorithms, and Applications,
PAMI(23), No. 10, October 2001, pp. 1144-1151.
IEEE DOI 0110
Extend the concept of a median to graphs. BibRef

Le Saux, B.[Bertrand], Bunke, H.[Horst],
Combining SVM and Graph Matching in a Bayesian Multiple Classifier System for Image Content Recognition,
SSPR06(696-704).
Springer DOI 0608
BibRef

Huet, B.[Benoit], Hancock, E.R.[Edwin R.],
Relational object recognition from large structural libraries,
PR(35), No. 9, September 2002, pp. 1895-1915.
Elsevier DOI 0206
BibRef

Huet, B., Hancock, E.R.,
Sensitivity Analysis for Object Recognition from Large Structural Libraries,
ICCV99(1137-1143).
IEEE DOI BibRef 9900

Huet, B.[Benoit], Hancock, E.R.[Edwin R.],
Fuzzy Relational Distance for Large-scale Object Recognition,
CVPR98(138-143).
IEEE DOI BibRef 9800

Huet, B.[Benoit], Hancock, E.R.[Edwin R.],
Line Pattern Retrieval Using Relational Histograms,
PAMI(21), No. 12, December 1999, pp. 1363-1370.
IEEE DOI 0001
BibRef
Earlier:
Relational Histograms for Shape Indexing,
ICCV98(563-569).
IEEE DOI Shape to retrieve line based patterns from a database. BibRef

Huet, B.[Benoit], Hancock, E.R.[Edwin R.],
Shape recognition from large image libraries by inexact graph matching,
PRL(20), No. 11-13, November 1999, pp. 1259-1269. 0001
BibRef
Earlier:
Inexact Graph Retrieval,
CBAIVL99(xx-yy). BibRef

Huet, B.[Benoit], Hancock, E.R.[Edwin R.],
Structurally Gated Pairwise Geometric Histograms for Shape Indexing,
BMVC97(xx-yy).
HTML Version. 0209
BibRef

Han, I.S.[In-Seo], Yun, I.D.[Il Dong], Lee, S.U.[Sang Uk],
Modified Hausdorff distance for model-based 3-D object recognition from a single view,
JVCIR(15), No. 1, March 2004, pp. 27-43.
Elsevier DOI 0402
BibRef
Earlier:
Model-based object recognition Using the Hausdorff Distance with Explicit Pairing,
ICIP99(IV:83-87).
IEEE DOI BibRef

Guru, D.S., Kiranagi, B.B.[Bapu B.], Nagabhushan, P.,
Multivalued type proximity measure and concept of mutual similarity value useful for clustering symbolic patterns,
PRL(25), No. 10, 16 July 2004, pp. 1203-1213.
Elsevier DOI 0407
BibRef

Guru, D.S., Kiranagi, B.B.[Bapu B.],
Multivalued type dissimilarity measure and concept of mutual dissimilarity value for clustering symbolic patterns,
PR(38), No. 1, January 2005, pp. 151-156.
Elsevier DOI 0410
BibRef

Wang, W.Q.[Wei-Qiong], Xin, X.L.[Xiao-Long],
Distance measure between intuitionistic fuzzy sets,
PRL(26), No. 13, 1 October 2005, pp. 2063-2069.
Elsevier DOI 0509
BibRef

Boran, F.E.[Fatih Emre],
Erratum to Distance measure between intuitionistic fuzzy sets,
PRL(30), No. 4, 1 March 2009, pp. 468.
Elsevier DOI 0903

See also Distance measure between intuitionistic fuzzy sets. BibRef

Chávez, E.[Edgar], Navarro, G.[Gonzalo], Baeza-Yates, R.[Ricardo], Marroquín, J.L.[José Luis],
Searching in metric spaces,
Surveys(33), No. 3, September 2001, pp. 273-321.
WWW Link. 0805
Survey, Distance Measures. BibRef

Bustos, B.[Benjamin], Navarro, G.[Gonzalo], Chávez, E.[Edgar],
Pivot selection techniques for proximity searching in metric spaces,
PRL(24), No. 14, October 2003, pp. 2357-2366.
Elsevier DOI 0307
BibRef

Chávez, E.[Edgar], Navarro, G.[Gonzalo],
A compact space decomposition for effective metric indexing,
PRL(26), No. 9, 1 July 2005, pp. 1363-1376.
Elsevier DOI 0506
BibRef

Téllez, E.S.[Eric Sadit], Chávez, E.[Edgar], Camarena-Ibarrola, A.[Antonio],
A Brief Index for Proximity Searching,
CIARP09(529-536).
Springer DOI 0911
BibRef

Xiao, Y.H.[Yang-Hua], Dong, H.[Hua], Wu, W.T.[Wen-Tao], Xiong, M.[Momiao], Wang, W.[Wei], Shi, B.[Baile],
Structure-based graph distance measures of high degree of precision,
PR(41), No. 12, December 2008, pp. 3547-3561.
Elsevier DOI 0810
Graph distance; Distance metric; Structure-based graph distance; SNP linkage disequilibrium BibRef

Chen, D.C.[De-Chang], Lu, C.T.[Chang-Tien], Kou, Y.F.[Yu-Feng], Chen, F.[Feng],
On Detecting Spatial Outliers,
GeoInfo(12), No. 4, December 2008, pp. xx-yy.
Springer DOI 0804
Find the objects whose non-spatial attribute values are significantly different from the values of their spatial neighbors. BibRef

Kim, D.H.[Duck Hoon], Yun, I.D.[Il Dong], Lee, S.U.[Sang Uk],
Attributed relational graph matching based on the nested assignment structure,
PR(43), No. 3, March 2010, pp. 914-928.
Elsevier DOI 1001
BibRef
Earlier:
A new attributed relational graph matching algorithm using the nested structure of earth mover's distance,
ICPR04(I: 48-51).
IEEE DOI 0409
Attributed relational graph (ARG); ARG matching; Assignment; Nested assignment structure; Relation vector space BibRef

Rezazadeh, S.[Soroosh], Coulombe, S.[Stéphane],
A novel discrete wavelet transform framework for full reference image quality assessment,
SIViP(7), No. 3, May 2013, pp. 559-573. 1305
BibRef
Earlier:
A novel approach for computing and pooling Structural SIMilarity index in the discrete wavelet domain,
ICIP09(2209-2212).
IEEE DOI 0911
BibRef

Salamat, N.[Nadeem], Zahzah, E.H.[El-Hadi],
On the improvement of combined fuzzy topological and directional relations information,
PR(45), No. 4, 2012, pp. 1559-1568.
Elsevier DOI 1410
Fuzzy Allen relations BibRef

Alioscha-Perez, M.[Mitchel], Sahli, H.[Hichem],
Efficient Learning of Spatial Patterns with Multi-Scale Conditional Random Fields for Region-Based Classification,
RS(6), No. 8, 2014, pp. 6727-6764.
DOI Link 1410
BibRef

Chai, L.[Li], Sheng, Y.X.[Yu-Xia],
Optimal Design of Multichannel Equalizers for the Structural Similarity Index,
IP(23), No. 12, December 2014, pp. 5626-5637.
IEEE DOI 1412
image restoration BibRef

Chai, L.[Li], Sheng, Y.X.[Yu-Xia], Zhang, J.X.[Jing-Xin],
Design of synthesis filter banks for the structural similarity index,
ICIP13(849-853)
IEEE DOI 1402
Closed-form solutions BibRef

Martinek, M.[Michael], Grosso, R.[Roberto], Greiner, G.[Günther],
Interactive partial 3D shape matching with geometric distance optimization,
VC(31), No. 2, February 2015, pp. 223-233.
WWW Link. 1503
BibRef

Berkels, B., Effland, A., Rumpf, M.,
Time Discrete Geodesic Paths in the Space of Images,
SIIMS(8), No. 3, 2015, pp. 1457-1488.
DOI Link 1511

See also Group Actions, Homeomorphisms, and Matching: A General Framework. BibRef

Nguyen, B.[Bac], Morell, C.[Carlos], de Baets, B.[Bernard],
Supervised distance metric learning through maximization of the Jeffrey divergence,
PR(64), No. 1, 2017, pp. 215-225.
Elsevier DOI 1701
Distance metric learning BibRef

Nguyen, B.[Bac], Morell, C.[Carlos], de Baets, B.[Bernard],
Distance metric learning with the Universum,
PRL(100), No. 1, 2017, pp. 37-43.
Elsevier DOI 1712
Metric learning BibRef

Sanakoyeu, A.[Artsiom], Bautista, M.A.[Miguel A.], Ommer, B.[Bjorn],
Deep unsupervised learning of visual similarities,
PR(78), 2018, pp. 331-343.
Elsevier DOI 1804
BibRef
Earlier: A2, A1, A3:
Deep Unsupervised Similarity Learning Using Partially Ordered Sets,
CVPR17(1923-1932)
IEEE DOI 1711
Visual similarity learning, Deep learning, Self-supervised learning, Human pose analysis, Object retrieval. Computational modeling, Standards, Training, Unsupervised learning, Visualization BibRef

Bay-Ahmed, H.A.[Hadj-Ahmed], Boudraa, A.O.[Abdel-Ouahab], Dare-Emzivat, D.[Delphine],
A Joint Spectral Similarity Measure for Graphs Classification,
PRL(120), 2019, pp. 1-7.
Elsevier DOI 1904
BibRef

Fishkind, D.E.[Donniell E.], Meng, L.Y.[Ling-Yao], Sun, A.[Ao], Priebe, C.E.[Carey E.], Lyzinski, V.[Vince],
Alignment strength and correlation for graphs,
PRL(125), 2019, pp. 295-302.
Elsevier DOI 1909
Correlated Bernoulli random graphs, Alignment strength, Graph correlation, Graph matchability, Complexity of graph matching BibRef

Moreno-García, C.F.[Carlos Francisco], Serratosa, F.[Francesc],
Generalised median of graph correspondences,
PRL(125), 2019, pp. 389-395.
Elsevier DOI 1909
BibRef

Ergün, A.[Asli], Ergun, S.[Serkan], Ünlü, M.Z.[Mehmet Zübeyir], Güngör, C.[Cengiz],
A saliency-weighted orthogonal regression-based similarity measure for entropic graphs,
SIViP(13), No. 7, October 2019, pp. 1377-1385.
Springer DOI 1911
BibRef

Ma, L.[Lin], Jiang, W.H.[Wen-Hao], Jie, Z.Q.[Ze-Qun], Jiang, Y.G.[Yu-Gang], Liu, W.[Wei],
Matching Image and Sentence With Multi-Faceted Representations,
CirSysVideo(30), No. 7, July 2020, pp. 2250-2261.
IEEE DOI 2007
Semantics, Neural networks, Vegetation, Forestry, Correlation, Stacking, Image retrieval, multi-faceted representations BibRef

Yu, T.[Tan], Meng, J.J.[Jing-Jing], Yang, M.[Ming], Yuan, J.S.[Jun-Song],
3D Object Representation Learning: A Set-to-Set Matching Perspective,
IP(30), 2021, pp. 2168-2179.
IEEE DOI 2102
3D object similarity measure. Kernel, Object recognition, Neural networks, Feature extraction, bilinear pooling BibRef

Xiao, F.Y.[Fu-Yuan],
A Distance Measure for Intuitionistic Fuzzy Sets and Its Application to Pattern Classification Problems,
SMCS(51), No. 6, June 2021, pp. 3980-3992.
IEEE DOI 2106
Q measurement, Fuzzy sets, Decision making, Task analysis, Measurement uncertainty, Distance measure, inference problems, uncertainty BibRef

Nguyen, D.H.[Dai Hai], Tsuda, K.[Koji],
On a linear fused Gromov-Wasserstein distance for graph structured data,
PR(138), 2023, pp. 109351.
Elsevier DOI 2303
Linear optimal transport, Graph structured data, Kernel method BibRef

Dong, Y.H.[Yi-Hao], Xu, X.L.[Xiao-Long],
Relational distance and document-level contrastive pre-training based relation extraction model,
PRL(167), 2023, pp. 132-140.
Elsevier DOI 2303
BibRef

Boria, N.[Nicolas], Kiederle, J.[Jana], Yger, F.[Florian], Blumenthal, D.B.[David B.],
The edge-preservation similarity for comparing rooted, unordered, node-labeled trees,
PRL(167), 2023, pp. 189-195.
Elsevier DOI 2303
Tree similarity measures, Integer quadratic programming, Approximation algorithms, RNA secondary structures BibRef

Lin, Y.J.[Yi-Jie], Yang, M.[Mouxing], Yu, J.[Jun], Hu, P.[Peng], Zhang, C.Q.[Chang-Qing], Peng, X.[Xi],
Graph Matching with Bi-level Noisy Correspondence,
ICCV23(23305-23314)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wang, R.Z.[Run-Zhong], Guo, Z.[Ziao], Jiang, S.F.[Shao-Fei], Yang, X.K.[Xiao-Kang], Yan, J.C.[Jun-Chi],
Deep Learning of Partial Graph Matching via Differentiable Top-K,
CVPR23(6272-6281)
IEEE DOI 2309
BibRef

Naumann, A.[Alexander], Hertlein, F.[Felix], Grimm, D.[Daniel], Zipfl, M.[Maximilian], Thoma, S.[Steffen], Rettinger, A.[Achim], Halilaj, L.[Lavdim], Luettin, J.[Juergen], Schmid, S.[Stefan], Caesar, H.[Holger],
Lanelet2 for nuScenes: Enabling Spatial Semantic Relationships and Diverse Map-based Anchor Paths,
E2EAD23(3248-3257)
IEEE DOI 2309
BibRef

Rica, E.[Elena], Álvarez, S.[Susana], Serratosa, F.[Francesc],
Learning Distances Between Graph Nodes and Edges,
SSSPR22(103-112).
Springer DOI 2301
BibRef

Sung, F.[Flood], Yang, Y.X.[Yong-Xin], Zhang, L.[Li], Xiang, T.[Tao], Torr, P.H.S.[Philip H.S.], Hospedales, T.M.[Timothy M.],
Learning to Compare: Relation Network for Few-Shot Learning,
CVPR18(1199-1208)
IEEE DOI 1812
Training, Measurement, Task analysis, Image recognition, Recurrent neural networks, Computer architecture BibRef

Yang, X.[Xu], Zhang, H.W.[Han-Wang], Cai, J.F.[Jian-Fei],
Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features,
ECCV18(XII: 38-54).
Springer DOI 1810
BibRef

Yin, G.J.[Guo-Jun], Sheng, L.[Lu], Liu, B.[Bin], Yu, N.H.[Neng-Hai], Wang, X.G.[Xiao-Gang], Shao, J.[Jing], Loy, C.C.[Chen Change],
Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition,
ECCV18(III: 330-347).
Springer DOI 1810
BibRef

Adamu, A.[Alhassan], Zainon, W.M.N.W.[Wan Mohd Nazmee Wan],
Similarity Assessment of UML Sequence Diagrams Using Dynamic Programming,
IVIC17(270-278).
Springer DOI 1711
BibRef

Veit, A.[Andreas], Belongie, S.[Serge], Karaletsos, T.[Theofanis],
Conditional Similarity Networks,
CVPR17(1781-1789)
IEEE DOI 1711
Extraterrestrial measurements, Kernel, Neural networks, Semantics, Visualization BibRef

Nagasawa, Y.[Yusuke], Nakamura, K.[Kazuaki], Nitta, N.[Naoko], Babaguchi, N.[Noboru],
Effect of Junk Images on Inter-concept Distance Measurement: Positive or Negative?,
MMMod17(II: 173-184).
Springer DOI 1701
BibRef

Piórkowski, R.[Rafal], Mantiuk, R.[Radoslaw],
Calibration of Structural Similarity Index Metric to Detect Artefacts in Game Engines,
ICCVG16(86-94).
Springer DOI 1611
BibRef

Zhu, P.F.[Peng-Fei], Zhang, L.[Lei], Zuo, W.M.[Wang-Meng], Zhang, D.[David],
From Point to Set: Extend the Learning of Distance Metrics,
ICCV13(2664-2671)
IEEE DOI 1403
BibRef

Wang, B.[Bin], Liu, Y.C.[Yun-Cai],
Discriminative probabilistic kernel learning for image retrieval,
ICIP13(2587-2591)
IEEE DOI 1402
GMMs BibRef

Wang, B.[Bin], Shen, Y.[Yi], Liu, Y.C.[Yun-Cai],
Integrating distance metric learning into label propagation model for multi-label image annotation,
ICIP11(3649-3652).
IEEE DOI 1201
BibRef

Fu, H.[Hao], Qiu, G.P.[Guo-Ping], He, H.[Hangen],
Feature Combination beyond Basic Arithmetics,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Duan, M.Y., Zang, Y., Pu, P.X., Shi, L.,
Geo-Info Graph Spectrum Analysis for Representing Distance Relations in GIS,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Šešelja, B.[Branimir], Tepavcevic, A.[Andreja],
Weak Fuzzy Equivalence and Equality Relations,
PReMI09(134-139).
Springer DOI 0912
BibRef

Sanroma, G.[Gerard], Serratosa, F.[Francesc], Alquezar, R.[Rene],
Improving the matching of graphs generated from shapes by the use of procrustes distances into a clique-based MAP formulation,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Rothaus, K.[Kai], Jiang, X.Y.[Xiao-Yi],
Constrained clustering by a novel graph-based distance transformation,
ICPR08(1-4).
IEEE DOI 0812
BibRef

May, T.[Thorsten], Kohlhammer, J.[Joern],
Visual Verification of Hypotheses,
ISVC08(II: 31-42).
Springer DOI 0812
Hypothesis verification. Match visual data with models. BibRef

Ochoa, A.[Alberto], Arco, L.[Leticia],
Differential Betweenness in Complex Networks Clustering,
CIARP08(227-234).
Springer DOI 0809
BibRef

Tian, Q.[Qi], Xue, Q.[Qing], Yu, J.[Jie], Sebe, N., Huang, T.S.[Thomas S.],
Toward an improved error metric,
ICIP04(IV: 2199-2202).
IEEE DOI 0505
BibRef

Climent, J., Aranda, J., Grau, A.[Antoni], Sanfeliu, A.,
Low Cost Architecture for Structure Measure Distance Computation,
ICPR98(Vol II: 1592-1594).
IEEE DOI 9808
BibRef

Azencott, R., Younes, L., Coldefy, F.,
A Distance for Elastic Matching in Object Recognition,
ICPR96(I: 687-691).
IEEE DOI 9608
(ENS Cachan CMLA, F) BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Evidence Theory, Combination Techniques, Optimization Techniques .