Tikhonov, A.N.,
The Regularization of Ill-Posed Problems,
Dokl. Akad. Nauk.(SSR 153), No. 1, 1963, pp. 49-52.
BibRef
6300
Arsenin, V.Y.,
Regularization Method,
USSR Computational Math(8), 1968.
BibRef
6800
Good, I.J.,
Gaskins, R.A.,
Nonparametric Roughness Penalties for Preobability Densities,
Biometrika(58), 1971, pp. 255-277.
BibRef
7100
Greig, D.,
Porteous, B.,
Seheult, A.,
Exact Maximum a Posterori Estimation for Binary Images,
RoyalStat(B: 51), No. 2, 1989, pp. 271-279.
Show min-cut/max-flow algorithms can be used to minimize energy
functions in vision.
BibRef
8900
Shahraray, B., and
Anderson, D.J.,
Optimal Estiamtion of Contour Properties by
Cross-Validated Regularization,
PAMI(11), No. 6, June 1989, pp. 600-610.
IEEE Abstract. IEEE Top Reference.
WWW Version. Analysis of parameters in regularization.
BibRef
8906
Lee, D., and
Pavlidis, T.,
One-Dimensional Regularization with Discontinuities,
PAMI(10), No. 6, November 1988, pp. 822-829.
IEEE Abstract. IEEE Top Reference.
WWW Version.
BibRef
8811
Earlier:
ICCV87(572-577).
BibRef
Terzopoulos, D.[Demetri],
Regularization of Inverse Visual Problems Involving Discontinuities,
PAMI(8), No. 4, July 1986, pp. 413-424.
A proposal of stabilizing functions for use in inverse vision
problems. There are a lot of references, and this may really go
with his relaxation papers.
BibRef
8607
Terzopoulos, D.[Demetri],
Visual Modelling,
BMVC91(xx-yy).
PDF Version.
9109
BibRef
Terzopoulos, D.[Demetri],
Controlled-Smoothness Stabilizers fo the Regularization of
Ill-Posed Visual Problems Involving Discontinuities,
DARPA84(225-229).
BibRef
8400
Poggio, T., and
Girosi, F.,
Regularization Algorithms for Learning That Are Equivalent to
Multilayer Networks,
Science(247), No. 4945, February 23, 1990.
BibRef
9002
Girosi, F.,
Jones, M.J.,
Poggio, T.,
Regularization Theory and Neural Networks Architectures,
NeurComp(7), No. 2, March 1995, pp. 219-269.
BibRef
9503
Poggio, T., and
Girosi, F.,
Networks for Approximation and Learning,
PIEEE(78), No. 9, September 1990, pp. 1481-1497.
BibRef
9009
Earlier:
A Theory of Networks for Approximation and Learning,
MIT AI-TR-1140, 1989.
BibRef
Poggio, T.A.,
Torre, V., and
Koch, C.,
Computational Vision and Regularization Theory,
Nature(317), 1985, pp. 314-319.
BibRef
8500
Earlier:
without A3:
Ill-Posed Problems and Regularization Analysis in Early Vision,
DARPA84(257-263).
BibRef
And:
MIT AI Memo-773, April 1984.
WWW Version.
Computational Vision. A presentation of the basics of regularization and what it is
intended to solve.
BibRef
Taratorin, A.M.,
Sideman, S.,
Constrained regularized differentiation,
PAMI(16), No. 1, January 1994, pp. 88-92.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0401
BibRef
Marroquin, J.L.[Jose L.],
Velasco, F.A.[Fernando A.],
Rivera, M.[Mariano], and
Nakamura, M.[Miguel],
Gauss-Markov Measure Field Models for Low-Level Vision,
PAMI(23), No. 4, April 2001, pp. 337-348.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0104Model using Bayesian Estimation Theory with prior MRF models. Applied to
segmentation, texture directions, classification, quantization.
BibRef
Marroquin, J.L.,
Mitter, S.K., and
Poggio, T.A.,
Probabilistic Solution of Ill-Posed Problems in Computational Vision,
ASAJ(82), No. 397, March 1987, pp. 76-89.
BibRef
8703
Earlier:
DARPA85(293-309).
BibRef
And:
MIT AI Memo-97, March 1987.
BibRef
Marroquin, J.L.,
Deterministic Bayesian Estimation of Markovian Random Fields with
Applications to Computational Vision,
ICCV87(597-601).
BibRef
8700
Marroquin, J.L.[Jose Luis],
Probabilistic Solution of Inverse Problems,
MIT AI-TR-860, September 1985.
BibRef
8509
Ph.D.Thesis. 1985.
WWW Version.
BibRef
Bertero, M.,
Poggio, T.A., and
Torre, V.,
Ill-Posed Problems in Early Vision,
PIEEE(76), No. 8, August 1988, pp. 869-889.
BibRef
8808
Earlier:
MIT AI Memo924, May 1987.
WWW Version.
BibRef
Poggio, T.A.,
Early Vision:
From Computational Structure to Algorithms and Parallel Hardware,
CVGIP(31), No. 2, August 1985, pp. 139-155.
WWW Version.
BibRef
8508
Verri, A.[Alessandro],
Poggio, T.[Tomaso],
Regularization Theory and Shape Constraints,
MIT AI Memo-916, September 1986.
BibRef
8609
Karayiannis, N.B., and
Venetsanopoulos, A.N.,
Regularization Theory in Image Restoration:
The Stabilizing Functional Approach,
ASSP(38), No. 7, July 1990, pp. 1155-1179.
BibRef
9007
Unser, M.,
Aldroubi, A., and
Eden, M.,
Recursive Regularization Filters: Design, Properties, and Applications,
PAMI(13), No. 3, March 1991, pp. 272-277.
IEEE Abstract. IEEE Top Reference.
WWW Version.
BibRef
9103
Thompson, A.M.,
Brown, J.C.,
Kay, J.W., and
Titterington, D.M.,
A Study of Methods of Choosing the Smoothing
Parameter in Image Restoration by Regularization,
PAMI(13), No. 4, April 1991, pp. 326-339.
IEEE Abstract. IEEE Top Reference.
WWW Version.
BibRef
9104
Archer, G.,
Titterington, D.M.,
On Some Bayesian/Regularization Methods for Image Restoration,
IP(4), No. 7, July 1995, pp. 989-995.
IEEE DOI may work or IEEE-CS DOI may work.
0402
Restoration.
See also Bayesian Image Restoration: An Application to Edge-Preserving Surface Recovery.
BibRef
Tanaka, K.,
Titterington, D.M.,
Probabilistic image processing based on the Q-ising model by means of
the mean field method and loopy belief propagation,
ICPR04(II: 40-43).
IEEE DOI may work or IEEE-CS DOI may work.
0409
BibRef
Kang, M.G.,
Katsaggelos, A.K.,
General Choice of the Regularization Functional in
Regularized Image-Restoration,
IP(4), No. 5, May 1995, pp. 594-602.
IEEE DOI may work or IEEE-CS DOI may work.
See also Simultaneous Multichannel Image Restoration and Estimation of the Regularization Parameters.
BibRef
9505
Kang, M.G.,
Katsaggelos, A.K.,
Simultaneous Multichannel Image Restoration and Estimation of the
Regularization Parameters,
IP(6), No. 5, May 1997, pp. 774-778.
IEEE DOI may work or IEEE-CS DOI may work.
9705
See also General Choice of the Regularization Functional in Regularized Image-Restoration.
BibRef
Hong, M.C.,
Kang, M.G., and
Katsaggelos, A.K.,
An Iterative Weighted Regularized Algorithm for Improving the Resolution
of Video Sequences,
ICIP97(II: 474-477).
IEEE DOI may work or IEEE-CS DOI may work.
BibRef
9700
Shulman, D.,
Regularization of Inverse Problems in Low-Level
Vision While Preserving Discontinuities,
Ph.D.Thesis (CS), Univ. of Maryland, August 1990.
How to deal with edges in a regularization function.
BibRef
9008
Stevenson, R.L.,
Schmitz, B.E.,
Delp, E.J.,
Discontinuity Preserving Regularization of Inverse Visual Problems,
SMC(24), No. 3, March 1994, pp. 455-469.
BibRef
9403
Stevenson, R.L.[Robert L.], and
Delp, E.J.[Edward J.],
Fitting Curves with Discontinuities,
Robust90(xx).
BibRef
9000
Reeves, S.J., and
Higdon, A.C.,
Perceptual Evaluation of the Mean Square Error Choice of
Regularization Parameter,
IP(4), No. 1, January 1995, pp. 107-110.
IEEE DOI may work or IEEE-CS DOI may work. Human evaluation of the results.
BibRef
9501
Li, S.Z.,
On Discontinuity-Adaptive Smoothness Priors in Computer Vision,
PAMI(17), No. 6, June 1995, pp. 576-586.
IEEE Abstract. IEEE Top Reference.
WWW Version.
Surface Reconstruction.
Adaptive Smoothing.
BibRef
9506
O'Sullivan, J.A.,
Roughness penalties on finite domains,
IP(4), No. 9, September 1995, pp. 1258-1268.
IEEE DOI may work or IEEE-CS DOI may work.
0402Penalty functions in Regularization.
BibRef
Lin, L.C.,
Kuo, C.C.J.,
On Theory and Regularization of Scale-Limited Extrapolation,
SP(54), No. 3, November 1996, pp. 225-237.
9701
BibRef
Charbonnier, P.,
Blanc-Feraud, L.,
Aubert, G.,
Barlaud, M.,
Deterministic Edge-Preserving Regularization in Computed Imaging,
IP(6), No. 2, February 1997, pp. 298-311.
IEEE DOI may work or IEEE-CS DOI may work.
9703
BibRef
Earlier:
Two deterministic half-quadratic regularization algorithms for computed
imaging,
ICIP94(II: 168-172).
IEEE DOI may work or IEEE-CS DOI may work.
9411
BibRef
Koulibaly, P.M.,
Charbonnier, P.,
Blanc-Feraud, L.,
Laurette, I.,
Darcourt, J.,
Barlaud, M.,
Poisson statistic and half-quadratic regularization for emission
tomography reconstruction algorithm,
ICIP96(II: 729-732).
IEEE DOI may work or IEEE-CS DOI may work.
9610
BibRef
Blanc-Feraud, L.,
Charbonnier, P.,
Aubert, G.,
Barlaud, M.,
Nonlinear image processing: modeling and fast algorithm for
regularization with edge detection,
ICIP95(I: 474-477).
IEEE DOI may work or IEEE-CS DOI may work.
9510
BibRef
Aubert, G.,
Barlaud, M.,
Blanc-Feraud, L.,
Charbonnier, P.,
A deterministic algorithm for edge-preserving computed imaging using
Legendre transform,
ICPR94(C:188-191).
IEEE DOI may work or IEEE-CS DOI may work.
9410
BibRef
Nikolova, M.,
Idier, J.,
Mohammad-Djafari, A.,
Inversion of Large-Support Ill-Posed Linear-Operators Using a
Piecewise Gaussian MRF,
IP(7), No. 4, April 1998, pp. 571-585.
IEEE DOI may work or IEEE-CS DOI may work.
9804
BibRef
Radmoser, E.[Esther],
Scherzer, O.[Otmar],
Weickert, J.[Joachim],
Scale-Space Properties of Nonstationary Iterative Regularization
Methods,
JVCIR(11), No. 2, June 2000, pp. 96-114.
0008
BibRef
Earlier:
Scale-Space Properties of Regularization Methods,
ScaleSpace99(211-222).
BibRef
Gader, P.D.[Paul D.],
Khabou, M.A.[Mohamed A.],
Koldobsky, A.[Alexander],
Morphological regularization neural networks,
PR(33), No. 6, June 2000, pp. 935-944.
WWW Version.
0004
BibRef
Raudys, S.[Sarunas],
Scaled rotation regularization,
PR(33), No. 12, December 2000, pp. 1989-1998.
WWW Version.
0008
BibRef
de Micheli, E.[Enrico],
Viano, G.A.[Giovanni Alberto],
Probabilistic regularization in inverse optical imaging,
JOSA-A(17), No. 11, November 2000, pp. 1942-1951.
0011
BibRef
Chambolle, A.,
Lucier, B.J.,
Interpreting translation-invariant wavelet shrinkage as a new image
smoothing scale space,
IP(10), No. 7, July 2001, pp. 993-1000.
IEEE DOI may work or IEEE-CS DOI may work.
0108
BibRef
Rivera, M.[Mariano],
Marroquin, J.L.[Jose L.],
Efficient half-quadratic regularization with granularity control,
IVC(21), No. 4, April 2003, pp. 345-357.
WWW Version.
0301
BibRef
Hinterberger, W.[Walter],
Hintermüller, M.[Michael],
Kunisch, K.[Karl],
von Oehsen, M.[Markus],
Scherzer, O.[Otmar],
Tube Methods for BV Regularization,
JMIV(19), No. 3, November 2003, pp. 219-235.
WWW Version.
0310Bounded variation regularization.
BibRef
Scherzer, O.[Otmar],
Taut-String Algorithm and Regularization Programs with G-Norm Data Fit,
JMIV(23), No. 2, September 2005, pp. 135-143.
WWW Version.
0505
BibRef
Fuchs, M.[Matthias],
Scherzer, O.[Otmar],
Regularized Reconstruction of Shapes with Statistical a priori
Knowledge,
IJCV(79), No. 2, August 2008, pp. xx-yy.
WWW Version.
0711
BibRef
Figueiredo, M.A.T.[Mario A.T.],
Hancock, E.R.[Edwin R.],
Pelillo, M.[Marcello],
Zerubia, J.B.[Josiane B.],
Guest editors' Introduction to the special section on energy
minimization methods in computer vision and pattern recognition,
PAMI(25), No. 11, November 2003, pp. 1361-1363.
IEEE Abstract. IEEE Top Reference.
BibRef
0311
And:
PAMI(26), No. 2, February 2004, pp. 145-146.
IEEE Abstract. IEEE Top Reference.
0311Pose the task as the minimization of an energy measure,
then a variety of optimization methods can be applied.
Includes relaxation, regularization, active contours, Markov models.
BibRef
Vanzella, W.[Walter],
Pellegrino, F.A.[Felice Andrea],
Torre, V.[Vincent],
Self-Adaptive Regularization,
PAMI(26), No. 6, June 2004, pp. 804-809.
IEEE Abstract. IEEE Top Reference.
0404Adapting the parameters for Mumford-Shah
See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. to
optimize details.
BibRef
Shkvarko, Y.V.,
Unifying Regularization and Bayesian Estimation Methods for Enhanced
Imaging With Remotely Sensed Data-Part I: Theory,
GeoRS(42), No. 5, May 2004, pp. 923-931.
IEEE Abstract. IEEE Top Reference.
0407
BibRef
Shkvarko, Y.V.,
Unifying Regularization and Bayesian Estimation Methods for Enhanced
Imaging With Remotely Sensed Data-Part II: Implementation and
Performance Issues,
GeoRS(42), No. 5, May 2004, pp. 932-940.
IEEE Abstract. IEEE Top Reference.
0407
BibRef
Shkvarko, Y.V.[Yuriy V.],
Vazquez-Bautista, R.[Rene],
Villalon-Turrubiates, I.E.[Ivan E.],
Fusion of Bayesian Maximum Entropy Spectral Estimation and Variational
Analysis Methods for Enhanced Radar Imaging,
ACIVS07(109-120).
WWW Version.
0708
BibRef
Shkvarko, Y.V.[Yuri V.],
Netjukhailo, A.S.[Alexey S.],
Fusion of Bayesian estimation and MTF inversion techniques for improved
array imaging in scattering media,
CAIP95(526-531).
WWW Version.
9509
BibRef
Shkvarko, Y.V.,
Leyva-Montiel, J.L.,
Villalon-Turrubiates, I.E.[Ivan E.],
Unifying the Experiment Design and Constrained Regularization Paradigms
for Reconstructive Imaging with Remote Sensing Data,
ICIP06(3241-3244).
0610
IEEE DOI may work or IEEE-CS DOI may work.
BibRef
Viéville, T.[Thierry],
An unbiased implementation of regularization mechanisms,
IVC(23), No. 11, 1 October 2005, pp. 981-998.
WWW Version.
0510
BibRef
Viéville, T.[Thierry],
Biologically plausible regularization mechanisms,
INRIARR-4625, Novembre 2002.
HTML Version.
0306
BibRef
Gutierrez, J.,
Ferri, F.J.,
Malo, J.,
Regularization Operators for Natural Images Based on Nonlinear
Perception Models,
IP(15), No. 1, January 2006, pp. 189-200.
IEEE DOI may work or IEEE-CS DOI may work.
0601
BibRef
Allain, M.,
Idier, J.,
Goussard, Y.,
On Global and Local Convergence of Half-Quadratic Algorithms,
IP(15), No. 5, May 2006, pp. 1130-1142.
IEEE DOI may work or IEEE-CS DOI may work.
0605
BibRef
Earlier:
ICIP02(II: 833-836).
IEEE Abstract. IEEE Top Reference.
0210
BibRef
Mignotte, M.,
A Segmentation-Based Regularization Term for Image Deconvolution,
IP(15), No. 7, July 2006, pp. 1973-1984.
IEEE DOI may work or IEEE-CS DOI may work.
0606
BibRef
Earlier:
An Adaptive Segmentation-Based Regularization Term for Image
Restoration,
ICIP05(I: 901-904).
IEEE DOI may work or IEEE-CS DOI may work.
0512
BibRef
He, L.[Lin],
Burger, M.[Martin],
Osher, S.J.[Stanley J.],
Iterative Total Variation Regularization with Non-Quadratic Fidelity,
JMIV(26), No. 1-2, November 2006, pp. 167-184.
WWW Version.
0701 See also Variational Problems and Partial Differential Equations on Implicit Surfaces.
BibRef
Xu, J.,
Osher, S.J.[Stanley J.],
Iterative Regularization and Nonlinear Inverse Scale Space Applied to
Wavelet-Based Denoising,
IP(16), No. 2, February 2007, pp. 534-544.
IEEE DOI may work or IEEE-CS DOI may work.
0702
BibRef
Grasmair, M.[Markus],
The Equivalence of the Taut String Algorithm and BV-Regularization,
JMIV(27), No. 1, January 2007, pp. 59-66.
WWW Version.
0702
BibRef
Lie, J.[Johan],
Nordbotten, J.M.[Jan M.],
Inverse Scale Spaces for Nonlinear Regularization,
JMIV(27), No. 1, January 2007, pp. 41-50.
WWW Version.
0702
BibRef
Laligant, O.,
Truchetet, F.,
Meriaudeau, F.,
Regularization Preserving Localization of Close Edges,
SPLetters(14), No. 3, March 2007, pp. 185-188.
IEEE DOI may work or IEEE-CS DOI may work.
0703
BibRef
Le Hgarat-Mascle, S.,
Kallel, A.,
Descombes, X.,
Ant Colony Optimization for Image Regularization Based on a
Nonstationary Markov Modeling,
IP(16), No. 3, March 2007, pp. 865-878.
IEEE DOI may work or IEEE-CS DOI may work.
0703
BibRef
Bioucas-Dias, J.M.[Jose M.],
Figueiredo, M.A.T.[Mario A. T.],
A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for
Image Restoration,
IP(16), No. 12, December 2007, pp. 2992-3004.
IEEE DOI may work or IEEE-CS DOI may work.
0711
BibRef
Earlier:
Two-Step Algorithms for Linear Inverse Problems with Non-Quadratic
Regularization,
ICIP07(I: 105-108).
IEEE DOI may work or IEEE-CS DOI may work.
0709
BibRef
Steinke, F.[Florian],
Scholkopf, B.[Bernhard],
Kernels, regularization and differential equations,
PR(41), No. 11, November 2008, pp. 3271-3286.
WWW Version.
0808Positive definite kernel; Differential equation; Gaussian process;
Reproducing kernel Hilbert space
BibRef
Chartrand, R.[Rick],
Nonconvex Regularization for Shape Preservation,
ICIP07(I: 293-296).
IEEE DOI may work or IEEE-CS DOI may work.
0709
BibRef
Chang, H.H.[Hsun-Hsien],
Moura, J.M.F.[Jose M. F.],
Classification by Cheeger Constant Regularization,
ICIP07(II: 209-212).
IEEE DOI may work or IEEE-CS DOI may work.
0709
BibRef
Erdem, E.[Erkut],
Sancar-Yilmaz, A.[Aysun],
Tari, S.[Sibel],
Mumford-Shah Regularizer with Spatial Coherence,
SSVM07(545-555).
WWW Version.
0705
BibRef
Lin, Z.[Zhu],
Islam, M.S.,
An Adaptive Edge-Preserving Variational Framework for Color Image
Regularization,
ICIP05(I: 101-104).
IEEE DOI may work or IEEE-CS DOI may work.
0512
BibRef
Chan, R.H.,
Ho, C.W.[Chung-Wa],
Leung, C.Y.[Chun-Yee],
Nikolova, M.,
Minimization of Detail-preserving Regularization Functional by Newton's
Method with Continuation,
ICIP05(I: 125-128).
IEEE DOI may work or IEEE-CS DOI may work.
0512
BibRef
Zhou, D.Y.[Deng-Yong],
Schölkopf, B.[Bernhard],
Regularization on Discrete Spaces,
DAGM05(361).
WWW Version.
0509
BibRef
Florack, L.M.J.[Luc M.J.],
Codomain scale space and regularization for high angular resolution
diffusion imaging,
Tensor08(1-6).
IEEE DOI may work or IEEE-CS DOI may work.
0806
BibRef
Florack, L.M.J.,
Duits, R.[Remco],
Bierkens, J.,
Tikhonov regularization versus scale space: A new result,
ICIP04(I: 271-274).
IEEE DOI may work or IEEE-CS DOI may work.
0505
BibRef
Huang, X.F.[Xiao-Fei],
Cooperative Optimization for Energy Minimization in Computer Vision:
A Case Study of Stereo Matching,
DAGM04(302-309).
WWW Version.
0505
BibRef
Yang, C.J.[Chang-Jiang],
Duraiswami, R.,
Davis, L.S.,
Near-optimal regularization parameters for applications in computer
vision,
ICPR02(II: 569-573).
IEEE DOI may work or IEEE-CS DOI may work.
0211
BibRef
Nikolova, M.,
Ng, M.,
Comparison of the main forms of half-quadratic regularization,
ICIP02(I: 349-352).
IEEE Abstract. IEEE Top Reference.
0210
BibRef
Toh, K.A.[Kar-Ann],
Global Energy Minimization: A Transformation Approach,
EMMCVPR02(391 ff.).
HTML Version.
0205
BibRef
Oraintara, S.,
Karl, W.C.,
Castanon, D.A.,
Nguyen, T.,
A Method for Choosing the Regularization Parameter in Generalized
Tikhonov Regularized Linear Inverse Problems,
ICIP00(Vol I: 93-96).
IEEE Abstract. IEEE Top Reference.
0008
BibRef
Yang, Z.Y.[Zhi-Yong],
Ma, S.D.[Song-De],
Beyond standard regularization theory,
CAIP97(289-296).
WWW Version.
9709
BibRef
Froehlinghaus, T.,
Buhmann, J.,
Regularizing Phase Based Stereo,
ICPR96(I: 451-455).
IEEE DOI may work or IEEE-CS DOI may work.
9608(Rheinische Fr.-Wihelms-Univ., D)
BibRef
Gunsel, B.,
Guzelis, C.,
Supervised learning of smoothing parameters in image restoration by
regularization under cellular neural networks framework,
ICIP95(I: 470-473).
IEEE DOI may work or IEEE-CS DOI may work.
9510
BibRef
Howard, C.G.,
Bock, P.,
Using a hierarchical approach to avoid over-fitting in early vision,
ICPR94(A:826-829).
IEEE DOI may work or IEEE-CS DOI may work.
9410
BibRef
Boult, T.E.,
Optimal Algorithms: Tools for Mathematical Modeling,
Complexity(3), 1987, pp. 183-200.
BibRef
8700
And:
Using Optimal Algorithms to Test Model Assumptions in Computer Vision,
DARPA87(921-926).
BibRef
Boult, T.E.,
What is Regular in Regularization?,
ICCV87(457-462).
A look at regularization and some alternatives.
BibRef
8700
Szeliski, R.,
Regularization Uses Fractal Priors,
AAAI-87(749-754).
BibRef
8700
Hummel, R.,
Moniot, R.,
Solving Ill-Conditioned Problems by Minimizing Equation Error,
ICCV87(527-533).
BibRef
8700
Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
Connectionist Approaches to Computer Vision .