13.3.8 Graph Matching, Neural Networks, Hopfield Networks

Chapter Contents (Back)
Object Recognition. Constraint Satisfaction. Matching, Graphs. Matching, Hopfield Networks. Neural Networks. Hopfield Networks.

Hopfield, J.J., and Tank, D.W.,
Computing with Neural Circuits: A Model,
Science(233), August 8, 1986, pp. 625-633. BibRef 8608
And:
Neural Computations of Decisions in Optimization Problems,
BioCyber(52), 1985, pp. 141-152. BibRef

Hopfield, J.J.,
Neurons with Graded Response Have Collective Computational Properties Like Those of Two-State Neurons,
NAS(81), May 1984, pp. 3088-3092. BibRef 8405
And:
Neural Networks and Physical Systems with Emergent Collective Computational Abilities,
NAS(79), 1982, pp. 2554-2558. BibRef

Tank, D.W., and Hopfield, J.J.,
Simple 'neural' optimization networks: An A/D converter, signal decision circuit and a linear programming circuit,
CirSys(33), May 1986, pp. 533-541. Time continuous recurrent artificial neural network for optimization problems. BibRef 8605

Kamgar-Parsi, B., and Kamgar-Parsi, B.,
On Problem Solving with Hopfield Netowrks,
BioCyber(62), 1990, pp. 415-423. BibRef 9000

Ney, H.,
On the Probabilistic-Interpretation of Neural-Network Classifiers and Discriminative Training Criteria,
PAMI(17), No. 2, February 1995, pp. 107-119.
IEEE DOI Non-parametric classifiers and neural networks have similar properties. BibRef 9502

Suganthan, P.N., Teoh, E.K., Mital, D.P.,
Pattern-Recognition by Homomorphic Graph Matching Using Hopfield Neural Networks,
IVC(13), No. 1, February 1995, pp. 45-60.
Elsevier DOI BibRef 9502
And:
Self-Organizing Hopfield Network for Attributed Relational Graph Matching,
IVC(13), No. 1, February 1995, pp. 61-73.
Elsevier DOI BibRef

Suganthan, P.N., Teoh, E.K., Mital, D.P.,
Pattern-Recognition by Graph Matching Using the Potts MFT Neural Networks,
PR(28), No. 7, July 1995, pp. 997-1009.
Elsevier DOI Hopfield Networks. Mean-field annealing. BibRef 9507

Suganthan, P.N., Teoh, E.K., Mital, D.P.,
Optimal Mapping of Graph Homomorphism onto Self-Organizing Hopfield Network,
IVC(15), No. 9, September 1997, pp. 679-694.
Elsevier DOI 9709
BibRef

Wei, L., and Nasrabadi, N.M.,
Object Recognition Based on Graph Matching Implemented by a Hopfield-Style Neural Network,
IJCNNJune 1989, pp. II 287-290. Hopfield Networks. Matching that uses the Hopfield network as a parallel processing technique. BibRef 8906

Young, S.S.[Susan S.], Scott, P.D., Nasrabadi, N.M.,
Object Recognition Using Multilayer Hopfield Neural-Network,
IP(6), No. 3, March 1997, pp. 357-372.
IEEE DOI 9703
BibRef
Earlier: CVPR94(417-422).
IEEE DOI BibRef

Young, S.S.[Susan S.], Scott, P.D., Bandera, C.,
Foveal Automatic Target Recognition Using a Multiresolution Neural-Network,
IP(7), No. 8, August 1998, pp. 1122-1135.
IEEE DOI 9808
BibRef
Earlier:
Foveal Automatic Target Recognition Using a Neural Network,
ICIP96(I: 303-306).
IEEE DOI BibRef

Nasrabadi, N.M., Li, W.,
Object Recognition by a Hopfield Neural Network,
SMC(21), 1991, pp. 1523-1535. BibRef 9100
Earlier: Add A3: Choo, C.Y., ICCV90(325-328).
IEEE DOI 0403
BibRef

Yu, S.S.[Shiaw-Shian], Tsai, W.H.[Wen-Hsiang],
Relaxation by the Hopfield Neural Network,
PR(25), No. 2, February 1992, pp. 197-209.
Elsevier DOI BibRef 9202

Basak, J., Chaudhury, S., Pal, S.K., Majumder, D.D.[D. Dutta],
Matching of Structural Shape Descriptions with Hopfield Net,
PRAI(7), 1993, pp. 377-404. BibRef 9300

Chen, T.W.[Tsu Wang], and Lin, W.C.[Wei Chung],
A Neural-Network Approach to CSG-Based 3-D Object Recognition,
PAMI(16), No. 7, July 1994, pp. 719-726.
IEEE DOI BibRef 9407
Earlier: CVPR91(718-719).
IEEE DOI BibRef
Earlier: A2, A1:
CSG-Based Object Recognition Using Range Images,
ICPR88(I: 99-103).
IEEE DOI
See also Artificial Neural Networks for 3-D Motion Analysis I: Rigid Motion. BibRef

Lampinen, J., Oja, E.,
Distortion Tolerant Pattern-Recognition Based on Self-Organizing Feature-Extraction,
TNN(6), No. 3, May 1995, pp. 539-547. BibRef 9505

Salzberg, S., Delcher, A.L., Heath, D., Kasif, S.,
Best-Case Results for Nearest-Neighbor Learning,
PAMI(17), No. 6, June 1995, pp. 599-608.
IEEE DOI BibRef 9506

Cios, K.J., Shin, I.,
Image Recognition Neural-Network: IRNN,
NeurComp(7), No. 2, March 1995, pp. 159-185. BibRef 9503

Tseng, Y.H., Hwang, J.N., Sheehan, F.H.,
Three-Dimensional Object Representation and Invariant Recognition Using Continuous Distance Transform Neural Networks,
TNN(8), No. 1, January 1997, pp. 141-147. 9701
BibRef

Tseng, Y.H., Hwang, J.N., Sheehan, F.H.,
3-D Heart Modeling and Motion Estimation Based on Continuous Distance Transform Neural Networks and Affine Transform,
VLSIVideo(18), No. 3, April 1998, pp. 207-218. 9806
BibRef

Lee, J.S.[Jiann-Shu], Chen, C.H.[Chin-Hsing], Sun, Y.N.[Yung-Nien], Tseng, G.S.[Guan-Shu],
Occluded Objects Recognition Using Multiscale Features and Hopfield Neural-Network,
PR(30), No. 1, January 1997, pp. 113-122.
Elsevier DOI 9702
BibRef
Earlier:
Occluded objects recognition using multiscale features and Hopfield neural networks,
CIAP95(171-176).
Springer DOI 9509
BibRef

Huang, C.L.,
Parallel Image Segmentation Using Modified Hopfield Model,
PRL(13), 1992, pp. 345-353. BibRef 9200

Lades, M., Vorbrüggen, J.C., Buhmann, J.M., Lange, J., von der Malsburg, C.[Christoph], Würtz, R.P., and Konen, W.,
Distortion Invariant Object Recognition in the Dynamic Link Architecture,
TC(42), No. 3, March 1993, pp. 300-311.
IEEE DOI Face Recognition. Elastic Graph Matching. 93% over 300 examples. Elastic graphs, or a mesh of points. Deformable templates?
See also Object Recognition Robust Under Translations, Deformations, and Changes in Background. BibRef 9303

Kusnezow, W.[Witali], Horn, W.[Wilfried], Würtz, R.P.[Rolf P.],
Fast image processing with constraints by solving linear PDEs,
ELCVIA(6), No. 2, September 2007, pp. 22-36.
DOI Link 0803
BibRef

Westphal, G., Wurtz, R.P.,
Fast object and pose recognition through minimum entropy coding,
ICPR04(III: 53-56).
IEEE DOI 0409
BibRef

Cote, S., Tatnall, A.R.L.,
The Hopfield Neural-Network as a Tool for Feature Tracking and Recognition from Satellite Sensor Images,
JRS(18), No. 4, March 10 1997, pp. 871-885. 9703
BibRef

Shen, D.G., Ip, H.H.S.,
A Hopfield Neural-Network for Adaptive Image Segmentation: An Active Surface Paradigm,
PRL(18), No. 1, January 1997, pp. 37-48. 9704

See also Affine-Invariant Active Contour Model (AI-Snake) for Model-Based Segmentation, An. BibRef

Li, S.Z.[Stan Z.], Soh, W.Y.C.[William Y.C.], Teoh, E.K.[Eam Khwang],
Relaxation Labeling Using Augmented Lagrange-Hopfield Method,
PR(31), No. 1, January 1998, pp. 73-81.
Elsevier DOI 9802
BibRef

Li, S.Z.,
Relaxation labeling using Lagrange-Hopfield method,
ICIP95(I: 266-269).
IEEE DOI 9510
BibRef

Achour, K.[Karim], Mahiddine, L.[Lyes],
Hopfield Neural Network Based Stereo Matching Algorithm,
JMIV(16), No. 1, January 2002, pp. 17-29.
DOI Link 0202
BibRef

Li, W.J.[Wen-Jing], Lee, T.[Tong],
Object recognition and articulated object learning by accumulative Hopfield matching,
PR(35), No. 9, September 2002, pp. 1933-1948.
Elsevier DOI 0206
BibRef

Bagdanov, A.D.[Andrew D.], Worring, M.[Marcel],
First order Gaussian graphs for efficient structure classification,
PR(36), No. 6, June 2003, pp. 1311-1324.
Elsevier DOI 0304
BibRef


Li, W.J., Lee, T., Tsui, H.T.,
Image Analysis by Accumulative Hopfield Matching,
ICPR00(Vol II: 442-445).
IEEE DOI 0009
BibRef

Schaffer, M., Chen, T.,
Object Parts Matching Using Hopfield Neural Networks,
CAMP95(xx). BibRef 9500

Plakhov, A.Yu.,
The converging unlearning algorithm for the Hopfield neural network: optimal strategy,
ICPR94(B:104-106).
IEEE DOI 9410
BibRef

Parvin, B., and Medioni, G.G.,
A Dynamic System for Object Description and Correspondence,
CVPR91(393-399).
IEEE DOI BibRef 9100 USC Computer Vision BibRef
And: A1 only: Ph.D.Thesis (EE), July 1991, BibRef USC_IRISTR-286. Perceptual Grouping. Neural Network based approach to matching. Find boundary groupings in range data using corners, junctions and segments. BibRef

Parvin, B., and Medioni, G.G.,
A Layered Network for Correspondence of 3-D Objects,
CRA91(1808-1813). BibRef 9100 USC Computer Vision BibRef
Earlier:
A Constraint Satisfaction Network for Matching 3D Objects,
IJCNN89(281-286), Washington, DC, June 1989. BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Graph Matching, Continuous Relaxation, Constraint Satisfaction .


Last update:Mar 16, 2024 at 20:36:19