*Slagle, J.R.*,
*Lee, R.C.T.*,

**Applications of Game Tree Searching Techniques to
Sequential Pattern Recognition**,

*CACM(14)*, 1971, pp. 103-110.
BibRef
**7100**

*Haralick, R.M.*, and
*Shapiro, L.G.*,

**The Consistent Labeling Problem: Part I**,

*PAMI(1)*, No. 2, April 1979, pp. 173-184.
BibRef
**7904**

And:

**The Consistent Labeling Problem: Part II**,

*PAMI(2)*, No. 3, May 1980, pp. 193-203.
BibRef

Earlier:

**The Consistent Labeling Problem and Some Applications to
Scene Analysis**,

*ICPR78*(616-619).
BibRef

And:

**The Consistent Labeling Problem**,

*PRAI-78*(173-178).
Explore how the problem is done and various operators that
can make it faster.
BibRef

*Shapiro, L.G.*, and
*Haralick, R.M.*,

**Structural Descriptions and Inexact Matching**,

*PAMI(3)*, No. 5, September 1981, pp. 504-519.
BibRef
**8109**

Earlier:

**Algorithms for Inexact Matching**,

*ICPR80*(202-207).
*Relaxation, Evaluation*. Use of Null nodes.
This paper discusses structural description
methods (using parts and interrelationships of the parts), and
matching techniques based on tree searching (backtrack alone,
forwardchecking, and looking ahead). Two kind of matching are
described: exact where every relation matches and inexact that is
not perfect, only good enough (a mapping such that the weighted sum
of the corresponding relations is greater than some given threshold,
and the weighted sum of non-matching elements is less than a
threshold). Finding the best match is more complex: how do you
compare 2 matches when there are good and bad points to each?
Searching eliminates impossible (unlikely) paths by considering not
only the error in the matches found so far but the minimum error
that can occur in the future assignments as constrained by the past
labels. Forward checking looks at all future labels, looking ahead
only considers the next set of assignments. A look ahead by two
assignments is the same as discrete relaxation. The forward checking
produces the best results mostly because of the extra computation of
the lookahead operations. When more errors are introduced the
problem becomes much harder. A major conclusion of the paper is that
the inexact matching (consistent labeling) problem is much harder
than the exact matching problem.
BibRef

*Shapiro, L.G.*,

**Inexact Matching in ESP3**,

*ICPR76*(759-763).
BibRef
**7600**

*Haralick, R.M.*,
*Ullmann, J.R.*, and
*Shapiro, L.G.*,

**Computer Architecture for Solving Consistent Labeling Problems**,

*Computer Journal(28)*, No. 2, 1985, pp. 105-111.
BibRef
**8500**

*Haralick, R.M.[Robert M.]*, and
*Elliott, G.L.[Gordon L.]*,

**Increasing Tree Search Efficiency for Constraint Satisfaction Problems**,

*AI(14)*, No. 3, October 1980, pp. 263-313.

Elsevier DOI
BibRef
**8010**

Earlier:
*IJCAI79*(356-364).
BibRef

*Rubin, S.[Steve]*,

**Natural Scene Recognition Using Locus Search**,

*CGIP(13)*, No. 4, August 1980, pp. 298-333.

Elsevier DOI
BibRef
**8008**

*Rubin, S.*, and
*Reddy, R.*,

**The Locus Model of Search and its Use in Image Interpretation**,

*IJCAI77*(590-595).
BibRef
**7700**

And:
*DARPA77*(12-14).
Locus, or beam search applied to vision.
BibRef

*Rubin, S.[Steve]*,

**The ARGOS Image Understanding System**,

*Ph.D.*Thesis (CS), 1978.
BibRef
**7800**
*CMU-CS-TR*-Report, CMU CS Dept.
BibRef

Earlier:
*DARPAN78*(159-162).
*Pose Estimation*.
*Color*.
*Viewpoint Constraint*. The matching method used in HARPY speech program applied to vision,
recognition at the basic region level. It requires a detailed model
to specify what is possible.
BibRef

*Boyer, K.L.*,
*Vayda, A.J.*, and
*Kak, A.C.*,

**Robotic Manipulation Experiments Using Structural Stereopsis
for 3D Vision**,

*IEEE_EXPERT(1)*, Fall 1986, pp. 73-94.
This reports on results of the work that is
covered in the next paper, but is a less technical vision article.
BibRef
**8600**

*Boyer, K.L.*, and
*Kak, A.C.*,

**Structural Stereo for 3-D Vision**,

*PAMI(10)*, No. 2, March 1988, pp. 144-166.

IEEE DOI
BibRef
**8803**

Earlier:

**Symbolic Stereo from Structural Descriptions**,

*CAIA85*(82-87).
There is a lot in the paper, primarily it is a matching method. The
comparison technique is described in information theoretic terms,
but is basically standard, the difference is a triangle function
with a peak for no difference between the two and a limit on where
zero is reached. The search method is standard tree search, start
with the ones that have the fewest options (get the set of best
matches and take them only if they are good enough), also there is
a nice NIL mapping technique -- NIL is the match of last resort (i.e. at
the end of every path in the search tree) but is added to the possible
matches only if no other match is good enough. The system uses an
information theoretic distance measure (essentially the probaability that
two corresponding elements will have the given difference).
BibRef

*Vayda, A.J.*, and
*Kak, A.C.*,

**A Robot Vision System for Recognition of Generic Shaped Objects**,

*CVGIP(54)*, No. 1, July 1991, pp. 1-46.

Elsevier DOI
BibRef
**9107**

Earlier:

**INGEN: A Robot Vision System for Generic Object Recognition**,

*CADBV91*(166-175).
A generic object (parallelepipeds and cylinders) recognition system,
that extracts object hypotheses, geometric reasoning to find size
and detect geometric inconsistencies and recognition to reject
hypotheses which have little support. Uses range data.
BibRef

*van der Helm, P.A.*,
*Leeuwenberg, E.L.J.*,

**Avoiding explosive search in automatic selection of simplest pattern
codes**,

*PR(19)*, No. 2, 1986, pp. 181-191.

Elsevier DOI
**0309**

BibRef

*Newborn, M.*,

**Unsynchronized iteratively deepening parallel alpha-beta search**,

*PAMI(10)*, No. 5, September 1988, pp. 687-694.

IEEE DOI
**0401**

BibRef

*Schaeffer, J.*,

**The history heuristic and alpha-beta search enhancements in practice**,

*PAMI(11)*, No. 11, November 1989, pp. 1203-1212.

IEEE DOI
**0401**

BibRef

*Powley, C.*,
*Korf, R.E.*,

**Single-agent parallel window search**,

*PAMI(13)*, No. 5, May 1991, pp. 466-477.

IEEE DOI
**0401**

BibRef

*Kaindl, H.*,
*Shams, R.*,
*Horacek, H.*,

**Minimax search algorithms with and without aspiration windows**,

*PAMI(13)*, No. 12, December 1991, pp. 1225-1235.

IEEE DOI
**0401**

BibRef

*Yang, G.Z.[Guang-Zheng]*,

**The search algorithms stimulated by premise set in the syntactic
knowledge system**,

*PR(26)*, No. 1, January 1993, pp. 17-22.

Elsevier DOI
**0401**

BibRef

*Paglieroni, D.W.*,
*Ford, G.E.*,
*Tsujimoto, E.M.*,

**The Position-Orientation Masking Approach To Parametric
Search For Template Matching**,

*PAMI(16)*, No. 7, July 1994, pp. 740-747.

IEEE DOI
BibRef
**9407**

*Reinefeld, A.*,
*Marsland, T.A.*,

**Enhanced Iterative-Deepening Search**,

*PAMI(16)*, No. 7, July 1994, pp. 701-710.

IEEE DOI
BibRef
**9407**

*Ben-Arie, J.*, and
*Meiri, A.Z.*,

**3D Objects Recognition by Optimal Matching Search
of Multinary Relations Graphs**,

*CVGIP(37)*, No. 3, March 1987, pp. 345-361.

Elsevier DOI
*Recognize Three-Dimensional Objects*.
BibRef
**8703**

Earlier:

**3-D Objects Recognition by State Space Search:
Optimal Geometric Matching**,

*CVPR86*(456-461).
BibRef

And:

**Optimal Recognition of 3-D Objects By Search: Generic Models**,

*ICPR86*(100-103).
3D shape matching, using heuristics to limit the cost of the search.
(Ignore the grammar problems in the title.)
BibRef

*Ben-Arie, J.*, and
*Meiri, A.Z.*,

**Three-Dimensional Object Recognition by Two-Dimensional Inclined
Shapes Matching with Area Ratios Method**,

*Draft*fall 1984. (Technion - Israel) The
interesting thing is the ratio of the area of the lobe to the
whole area. This is the feature used in the comparison.
Everything else is straightforward.
BibRef
**8400**

*Kuno, Y.*,
*Okamoto, Y.*,
*Okada, S.*,

**Robot vision using a feature search strategy generated from a 3D object
model**,

*PAMI(13)*, No. 10, October 1991, pp. 1085-1097.

IEEE DOI
**0401**

BibRef

Earlier:

**Object Recognition Using a Feature Search Strategy Generated
from a 3-D Model**,

*ICCV90*(626-635).

IEEE DOI
BibRef

*Spirkovska, L.*,

**Three-Dimensional Object Recognition Using Similar Triangles
and Decision Trees**,

*PR(26)*, No. 5, May 1993, pp. 727-732.

Elsevier DOI
BibRef
**9305**

*Ishida, T.*,

**Real-Time Bidirectional Search:
Coordinated Problem-Solving in Uncertain Situations**,

*PAMI(18)*, No. 6, June 1996, pp. 617-628.

IEEE DOI
**9607**

Search.
BibRef

*Chaudhury, S.*,
*Acharyya, A.*,
*Subramanian, S.*,
*Parthasarathy, G.*,

**Recognition of Occluded Objects with Heuristic Search**,

*PR(23)*, No. 6, 1990, pp. 617-635.

Elsevier DOI
BibRef
**9000**

*Chaudhury, S.*,
*Subramanian, S.*,
*Parthasarathy, G.*,

**Recognition of Partial Planar Shapes in Limited Memory Environments**,

*PRAI(4)*, 1990, pp. 603-628.
BibRef
**9000**

*Ishida, T.*,
*Korf, R.E.*,

**Moving-Target Search: A Real-Time Search for Changing Goals**,

*PAMI(17)*, No. 6, June 1995, pp. 609-619.

IEEE DOI
BibRef
**9506**

*Cho, C.J.*,
*Kim, J.H.*,

**Recognizing 3-D Objects by Forward Checking Constrained Tree Search**,

*PRL(13)*, 1992, pp. 587-597.
BibRef
**9200**

*Stewart, B.S.*,
*Liaw, C.F.*,
*White, III, C.C.*,

**A Bibliography of Heuristic Search Research Through 1992**,

*SMC(24)*, 1994, pp. 268-293.
BibRef
**9400**

*Chung, K.L.*,
*Wu, J.G.*,
*Lan, J.K.*,

**Efficient Search Algorithm on Compact S-Trees**,

*PRL(18)*, No. 14, December 1997, pp. 1427-1434.
**9806**

BibRef

*Cantoni, V.*,
*Cinque, L.*,
*Guerra, C.*,
*Levialdi, S.*,
*Lombardi, L.*,

**2-D Object Recognition by Multiscale Tree Matching**,

*PR(31)*, No. 10, October 1998, pp. 1443-1454.

Elsevier DOI
**9808**

BibRef

*Raman, A.[Anand]*,
*Andreae, P.[Peter]*,
*Patrick, J.[Jon]*,

**A Beam Search Algorithm for PFSA Inference**,

*PAA(1)*, No. 2, 1998, pp. 121-129.
BibRef
**9800**

*Joseph, S.H.*,

**Analysing and reducing the cost of exhaustive correspondence search**,

*IVC(17)*, No. 11, September 1999, pp. 815-830.

Elsevier DOI
BibRef
**9909**

*Pridmort, T.P.*,
*Joseph, S.H.*,

**Integrating visual search with visual memory in a knowledge directed
image interpretation system**,

*BMVC90*(xx-yy).

PDF File.
**9009**

BibRef

*Silvela, J.*,
*Portillo, J.*,

**Breadth-first search and its application image processing problems**,

*IP(10)*, No. 8, August 2001, pp. 1194-1199.

IEEE DOI
**0108**

BibRef

*Wang, J.K.[Jian-Kang]*,
*Li, X.B.[Xiao-Bo]*,

**Controlled accurate searches with balloons**,

*PR(36)*, No. 3, March 2003, pp. 827-843.

Elsevier DOI
**0301**

BibRef

*Breuel, T.M.*,

**On the use of interval arithmetic in geometric branch and bound
algorithms**,

*PRL(24)*, No. 9-10, June 2003, pp. 1375-1384.

Elsevier DOI
**0304**

BibRef

*Breuel, T.M.[Thomas M.]*,

**A Comparison of Search Strategies for Geometric Branch and Bound
Algorithms**,

*ECCV02*(III: 837 ff.).

Springer DOI
**0205**

BibRef

*Breuel, T.M.[Thomas M.]*,

**Implementation techniques for geometric branch-and-bound matching
methods**,

*CVIU(90)*, No. 3, June 2003, pp. 258-294.

Elsevier DOI
**0307**

BibRef

*Sun, C.M.[Chang-Ming]*,
*Pallottino, S.[Stefano]*,

**Circular shortest path in images**,

*PR(36)*, No. 3, March 2003, pp. 709-719.

Elsevier DOI
**0301**

BibRef

Earlier:

**Circular Shortest Path on Regular Grids**,

*ACCV02*(852-857).
BibRef

*Appleton, B.[Ben]*,
*Sun, C.M.[Chang-Ming]*,

**Circular shortest paths by branch and bound**,

*PR(36)*, No. 11, November 2003, pp. 2513-2520.

Elsevier DOI
**0309**

BibRef

*Sun, C.M.[Chang-Ming]*,
*Appleton, B.[Ben]*,

**Multiple Paths Extraction in Images Using a Constrained Expanded
Trellis**,

*PAMI(27)*, No. 12, December 2005, pp. 1923-1933.

IEEE DOI
**0512**

Extract multiple paths, rather than a single optimal path.
(

See also Finding the Best Set of K Paths through a Trellis with Application to Multitarget Tracking. )
BibRef

*Undeger, C.*,
*Polat, F.*,

**Real-Time Edge Follow: A Real-Time Path Search Approach**,

*SMC-C(37)*, No. 5, September 2007, pp. 860-872.

IEEE DOI
**0710**

Real-time path searching. Compared to real-time A*.
BibRef

*Undeger, C.*,
*Polat, F.*,

**Real-Time Moving Target Evaluation Search**,

*SMC-C(39)*, No. 3, May 2009, pp. 366-372.

IEEE DOI
**0904**

BibRef

*Ris, M.[Marcelo]*,
*Barrera, J.[Junior]*,
*Martins, Jr., D.C.[David C.]*,

**U-curve: A branch-and-bound optimization algorithm for U-shaped cost
functions on Boolean lattices applied to the feature selection problem**,

*PR(43)*, No. 3, March 2010, pp. 557-568.

Elsevier DOI
**1001**

Boolean lattice; Branch-and-bound algorithm; U-shaped curve; Feature
selection; Subset search; Optimal search
BibRef

*Reis, M.S.[Marcelo S.]*,
*Barrera, J.[Junior]*,

**Solving Problems in Mathematical Morphology through Reductions to the
U-Curve Problem**,

*ISMM13*(49-60).

Springer DOI
**1305**

BibRef

*Tsapanos, N.[Nikolaos]*,
*Tefas, A.[Anastasios]*,
*Pitas, I.[Ioannis]*,

**Online shape learning using binary search trees**,

*IVC(28)*, No. 7, July 2010, pp. 1146-1154.

Elsevier DOI
**1006**

Incremental learning techniques; Online pattern recognition; Binary
search trees
Binary tree for storage and matching of templates.
BibRef

*Liu, G.C.[Guang-Can]*,
*Lin, Z.C.[Zhou-Chen]*,
*Yan, S.C.[Shui-Cheng]*,
*Sun, J.[Ju]*,
*Yu, Y.[Yong]*,
*Ma, Y.[Yi]*,

**Robust Recovery of Subspace Structures by Low-Rank Representation**,

*PAMI(35)*, No. 1, January 2013, pp. 171-184.

IEEE DOI
**1212**

Subspace clustering.
BibRef

*Liu, G.C.[Guang-Can]*,
*Xu, H.*,
*Tang, J.*,
*Liu, Q.*,
*Yan, S.C.[Shui-Cheng]*,

**A Deterministic Analysis for LRR**,

*PAMI(38)*, No. 3, March 2016, pp. 417-430.

IEEE DOI
**1602**

Low-Rank Representation.
Coherence. Motion segmentation, saliency, face recognition.
BibRef

*Zheng, Y.Q.[Yin-Qiang]*,
*Liu, G.C.[Guang-Can]*,
*Sugimoto, S.[Shigeki]*,
*Yan, S.C.[Shui-Cheng]*,
*Okutomi, M.[Masatoshi]*,

**Practical low-rank matrix approximation under robust L1-norm**,

*CVPR12*(1410-1417).

IEEE DOI
**1208**

BibRef

*Zheng, Y.Q.[Yin-Qiang]*,
*Sugimoto, S.[Shigeki]*,
*Okutomi, M.[Masatoshi]*,

**Deterministically maximizing feasible subsystem for robust model
fitting with unit norm constraint**,

*CVPR11*(1825-1832).

IEEE DOI
**1106**

BibRef

*Htoo, H.[Htoo]*,
*Ohsawa, Y.[Yutaka]*,
*Sonehara, N.[Noboru]*,
*Sakauchi, M.[Masao]*,

**Incremental Single-Source Multi-Target A* Algorithm for LBS Based on
Road Network Distance**,

*IEICE(E96-D)*, No. 5, May 2013, pp. 1043-1052.

WWW Link.
**1305**

Shortest path in road network.
BibRef

*Perakis, P.*,
*Passalis, G.*,
*Theoharis, T.*,
*Kakadiaris, I.A.*,

**3D Facial Landmark Detection under Large Yaw and Expression Variations**,

*PAMI(35)*, No. 7, 2013, pp. 1552-1564.

IEEE DOI face recognition; 3D facial landmark detection;
principal curvature value; spin images;
Eigenvalues and eigenfunctions
**1307**

BibRef

*Bazin, J.C.*,
*Li, H.D.[Hong-Dong]*,
*Kweon, I.S.[In So]*,
*Demonceaux, C.*,
*Vasseur, P.*,
*Ikeuchi, K.*,

**A Branch-and-Bound Approach to Correspondence and Grouping Problems**,

*PAMI(35)*, No. 7, 2013, pp. 1565-1576.

IEEE DOI
**1307**

object recognition; tree searching
BibRef

*Antikainen, H.[Harri]*,

**Using the Hierarchical Pathfinding A* Algorithm in GIS to Find Paths
through Rasters with Nonuniform Traversal Cost**,

*IJGI(2)*, No. 4, 2013, pp. 996-1014.

DOI Link
**1310**

BibRef

*Chen, B.Y.*,
*Lam, W.H.K.*,
*Li, Q.*,
*Sumalee, A.*,
*Yan, K.*,

**Shortest Path Finding Problem in Stochastic Time-Dependent Road
Networks With Stochastic First-In-First-Out Property**,

*ITS(14)*, No. 4, 2013, pp. 1907-1917.

IEEE DOI
**1312**

Algorithm design and analysis
BibRef

*Yoon, S.*,
*Shim, D.H.*,

**SLPA*: Shape-Aware Lifelong Planning A* for Differential
Wheeled Vehicles**,

*ITS(16)*, No. 2, April 2015, pp. 730-740.

IEEE DOI
**1504**

Heuristic algorithms
BibRef

*Wu, F.[Fan]*,
*Fu, K.[Kun]*,
*Wang, Y.[Yang]*,
*Xiao, Z.B.[Zhi-Bin]*,

**A Graph-Based Min-# and Error-Optimal Trajectory Simplification
Algorithm and Its Extension towards Online Services**,

*IJGI(6)*, No. 1, 2017, pp. xx-yy.

DOI Link
**1702**

BibRef

*Pal, P.S.*,
*Kar, R.*,
*Mandal, D.*,
*Ghoshal, S.P.*,

**A hybrid backtracking search algorithm with wavelet mutation-based
nonlinear system identification of Hammerstein models**,

*SIViP(11)*, No. 5, July 2017, pp. 921-928.

WWW Link.
**1706**

BibRef

*Pinheiro, M.A.[Miguel Amavel]*,
*Kybic, J.[Jan]*,
*Fua, P.[Pascal]*,

**Geometric Graph Matching Using Monte Carlo Tree Search**,

*PAMI(39)*, No. 11, November 2017, pp. 2171-2185.

IEEE DOI
**1710**

BibRef

Earlier: A1, A2, Only:

**Geometrical graph matching using Monte Carlo tree search**,

*ICIP15*(3145-3149)

IEEE DOI
**1512**

Biomedical imaging, Computational modeling,
Image edge detection, Monte Carlo methods, Roads,
Geometric graph matching,
Monte Carlo tree search, curve descriptor, image registration
BibRef

*Ait Bouziaren, S.*,
*Aghezzaf, B.*,

**An Improved Augmented epsilon-Constraint and Branch-and-Cut Method to
Solve the TSP With Profits**,

*ITS(20)*, No. 1, January 2019, pp. 195-204.

IEEE DOI
**1901**

Optimization, Traveling salesman problems,
Approximation algorithms, Intelligent transportation systems,
e-constraint
BibRef

*Khoa, N.L.D.[Nguyen Lu Dang]*,
*Wang, Y.[Yang]*,
*Chawla, S.[Sanjay]*,

**Incremental commute time and its online applications**,

*PR(88)*, 2019, pp. 101-112.

Elsevier DOI
**1901**

Commute time, Random walks, Online learning, Anomaly detection,
Manifold learning
BibRef

*Seo, K.[Kwangwon]*,
*Ahn, J.H.[Jin-Hyun]*,
*Im, D.H.[Dong-Hyuk]*,

**Optimization of Shortest-Path Search on RDBMS-Based Graphs**,

*IJGI(8)*, No. 12, 2019, pp. xx-yy.

DOI Link
**1912**

BibRef

*Dimitrov, M.[Miroslav]*,
*Baitcheva, T.[Tsonka]*,
*Nikolov, N.[Nikolay]*,

**Efficient Generation of Low Autocorrelation Binary Sequences**,

*SPLetters(27)*, 2020, pp. 341-345.

IEEE DOI
**2003**

Aperiodic autocorrelation function, binary sequences,
peak sidelobe level (psl), shotgun hill climbing
BibRef

*Silva-Gálvez, A.*,
*Lara-Cárdenas, E.*,
*Amaya, I.*,
*Cruz-Duarte, J.M.*,
*Ortiz-Bayliss, J.C.*,

**A Preliminary Study on Score-based Hyper-heuristics for Solving the Bin
Packing Problem**,

*MCPR20*(318-327).

Springer DOI
**2007**

BibRef

*Zhang, J.L.[Ji-Lian]*,
*Wei, K.M.[Kai-Min]*,
*Deng, X.L.[Xue-Lian]*,

**Heuristic algorithms for diversity-aware balanced multi-way number
partitioning**,

*PRL(136)*, 2020, pp. 56-62.

Elsevier DOI
**2008**

Artificial intelligence, Number partitioning,
Heuristic algorithms, Balanced multi-way number partitioning
BibRef

*Liu, X.C.[Xing-Chi]*,
*Derakhshani, M.[Mahsa]*,
*Lambotharan, S.[Sangarapillai]*,
*van der Schaar, M.[Mihaela]*,

**Risk-Aware Multi-Armed Bandits With Refined Upper Confidence Bounds**,

*SPLetters(28)*, 2021, pp. 269-273.

IEEE DOI
**2102**

Signal processing algorithms, Indexes, Gaussian distribution,
Uncertainty, Random variables, Standards, Measurement uncertainty,
exploration and exploitation
BibRef

*Xu, X.P.[Xiang-Ping]*,
*Li, J.[Jun]*,
*Zhou, M.C.[Meng-Chu]*,

**Bi-Objective Colored Traveling Salesman Problems**,

*ITS(23)*, No. 7, July 2022, pp. 6326-6336.

IEEE DOI
**2207**

Color, Urban areas, Traveling salesman problems, Search problems,
Optimization, Statistics, Sorting,
variable neighborhood search
BibRef

*Wang, H.Y.[Huan-Yu]*,
*Qin, Z.Q.[Ze-Qun]*,
*Li, S.Y.[Song-Yuan]*,
*Li, X.[Xi]*,

**CoDiNet: Path Distribution Modeling With Consistency and Diversity
for Dynamic Routing**,

*PAMI(44)*, No. 10, October 2022, pp. 6011-6023.

IEEE DOI
**2209**

Path through network.
Routing, Computational modeling, Computational efficiency,
Training, Image color analysis, Recurrent neural networks, dynamic routing
BibRef

*Meng, X.H.[Xiang-Hu]*,
*Li, J.[Jun]*,
*Dai, X.Z.[Xian-Zhong]*,
*Dou, J.P.[Jian-Ping]*,

**Variable Neighborhood Search for a Colored Traveling Salesman Problem**,

*ITS(19)*, No. 4, April 2018, pp. 1018-1026.

IEEE DOI
**1804**

Biological cells, Color, Encoding, Genetic algorithms, Optimization,
Traveling salesman problems, Urban areas,
variable neighborhood search
BibRef

*Xu, X.P.[Xiang-Ping]*,
*Li, J.[Jun]*,
*Zhou, M.C.[Meng-Chu]*,

**Delaunay-Triangulation-Based Variable Neighborhood Search to Solve
Large-Scale General Colored Traveling Salesman Problems**,

*ITS(22)*, No. 3, March 2021, pp. 1583-1593.

IEEE DOI
**2103**

Urban areas, Traveling salesman problems, Image color analysis,
Color, Intelligent transportation systems, Search problems,
intelligent optimization
BibRef

*Zhou, Y.M.[Yang-Ming]*,
*Xu, W.Q.[Wen-Qiang]*,
*Fu, Z.H.[Zhang-Hua]*,
*Zhou, M.C.[Meng-Chu]*,

**Multi-Neighborhood Simulated Annealing-Based Iterated Local Search
for Colored Traveling Salesman Problems**,

*ITS(23)*, No. 9, September 2022, pp. 16072-16082.

IEEE DOI
**2209**

Urban areas, Color, Traveling salesman problems,
Simulated annealing, Biological cells, Upper bound, Robots,
colored traveling salesman problem
BibRef

*Fan, H.M.[Hou-Ming]*,
*Peng, W.H.[Wen-Hao]*,
*Ma, M.Z.[Meng-Zhi]*,
*Yue, L.J.[Li-Jun]*,

**Storage Space Allocation and Twin Automated Stacking Cranes
Scheduling in Automated Container Terminals**,

*ITS(23)*, No. 9, September 2022, pp. 14336-14348.

IEEE DOI
**2209**

Containers, Resource management, Cranes, Loading, Optimization, Safety,
Stacking, Automated container terminal, handshake area,
variable neighborhood search based hybrid genetic algorithm
BibRef

*Fan, A.X.[Ao-Xiang]*,
*Ma, J.Y.[Jia-Yi]*,
*Jiang, X.Y.[Xing-Yu]*,
*Ling, H.B.[Hai-Bin]*,

**Efficient Deterministic Search With Robust Loss Functions for
Geometric Model Fitting**,

*PAMI(44)*, No. 11, November 2022, pp. 8212-8229.

IEEE DOI
**2210**

Estimation, Computational modeling, Benchmark testing,
Search problems, Approximation algorithms, Analytical models, image matching
BibRef

*Wang, X.[Xiao]*,
*Chen, Z.[Zhe]*,
*Jiang, B.[Bo]*,
*Tang, J.[Jin]*,
*Luo, B.[Bin]*,
*Tao, D.C.[Da-Cheng]*,

**Beyond Greedy Search: Tracking by Multi-Agent Reinforcement
Learning-Based Beam Search**,

*IP(31)*, 2022, pp. 6239-6254.

IEEE DOI
**2210**

Target tracking, Tracking, Visualization, Search problems,
Reinforcement learning, Trajectory, Decision making, greedy search
BibRef

*Zhang, R.K.[Rong-Kai]*,
*Zhang, C.[Cong]*,
*Cao, Z.G.[Zhi-Guang]*,
*Song, W.[Wen]*,
*Tan, P.S.[Puay Siew]*,
*Zhang, J.[Jie]*,
*Wen, B.[Bihan]*,
*Dauwels, J.[Justin]*,

**Learning to Solve Multiple-TSP With Time Window and Rejections via
Deep Reinforcement Learning**,

*ITS(24)*, No. 1, January 2023, pp. 1325-1336.

IEEE DOI
**2301**

Task analysis, Costs, Routing, Reinforcement learning, Time factors,
Training data, Market research, Travelling salesman problem,
deep reinforcement learning
BibRef

*Wang, K.[Ke]*,
*Feng, B.R.[Bao-Rui]*,
*Ma, Y.[Ying]*,
*Lin, W.L.[Wen-Liang]*,
*Zhao, J.G.[Jin-Gui]*,

**List Encoding of Vector Perturbation Precoding**,

*SPLetters(30)*, 2023, pp. 478-482.

IEEE DOI
**2305**

Perturbation methods, Precoding, Optimization,
Signal processing algorithms, Search problems, VP
BibRef

*Ling, Z.X.[Zheng-Xuan]*,
*Zhang, Y.[Yu]*,
*Chen, X.[Xi]*,

**A Deep Reinforcement Learning Based Real-Time Solution Policy for the
Traveling Salesman Problem**,

*ITS(24)*, No. 6, June 2023, pp. 5871-5882.

IEEE DOI
**2306**

Urban areas, Real-time systems, Heuristic algorithms,
Reinforcement learning, Neural networks, Training,
traveling salesman
BibRef

*Chole, V.[Vikrant]*,
*Gadicha, V.[Vijay]*,

**Locust Mayfly Optimization-Tuned Neural Network for AI-Based Pruning in
Chess Game**,

*IJIG(23)*, No. 4 2023, pp. 2350028.

DOI Link
**2308**

BibRef

*Kim, G.[Geunu]*,
*Jin, H.W.[Hyun-Woo]*,
*Kim, M.[Mingi]*,
*Jang, K.[Kitae]*,
*Jang, I.G.[In Gwun]*,

**Loop-Wise Route Representation and Its Optimization Formulation for
Symmetric Traveling Salesman Problems**,

*ITS(24)*, No. 9, September 2023, pp. 9490-9500.

IEEE DOI
**2310**

BibRef

*Lee, J.[Jiho]*,
*Kim, E.[Eunwoo]*,

**Mitigating Search Interference With Task-Aware Nested Search**,

*IP(33)*, 2024, pp. 3102-3114.

IEEE DOI
**2405**

Task analysis, Interference, Search problems,
Computer architecture, Multitasking, Costs, Generators,
search interference
BibRef

IEEE DOI

Shortest path problem, Machine learning algorithms, Decision making, Semisupervised learning, Predictive models, Classification algorithms BibRef

*Gutiérrez, O.[Omar]*,
*Zamora, E.[Erik]*,
*Menchaca, R.[Ricardo]*,

**Graph Representation for Learning the Traveling Salesman Problem**,

*MCPR21*(153-162).

Springer DOI
**2108**

BibRef

*Cai, Z.P.[Zhi-Peng]*,
*Chin, T.*,
*Koltun, V.*,

**Consensus Maximization Tree Search Revisited**,

*ICCV19*(1637-1645)

IEEE DOI
**2004**

*Code, Search*.

WWW Link. computational complexity, optimisation,
tree searching, consensus maximization tree structure,
Computational modeling
BibRef

*Bauer, D.[Dominik]*,
*Patten, T.[Timothy]*,
*Vincze, M.[Markus]*,

**SporeAgent: Reinforced Scene-level Plausibility for Object Pose
Refinement**,

*WACV22*(196-204)

IEEE DOI
**2202**

BibRef

Earlier:

**Monte Carlo Tree Search on Directed Acyclic Graphs for Object Pose
Verification**,

*CVS19*(386-396).

Springer DOI
**1912**

Visualization, Codes, Reinforcement learning,
Robustness, Iterative methods,
Vision for Robotics
BibRef

*Behzadi, S.*,
*Kolbadinejad, M.*,

**Introducing a Novel Method to Solve Shortest Path Problems Based On
Structure of Network Using Genetic Algorithm**,

*SMPR19*(201-203).

DOI Link
**1912**

BibRef

*Osmanlioglu, Y.[Yusuf]*,
*Shokoufandeh, A.[Ali]*,

**Multi-layer Tree Matching Using HSTs**,

*GbRPR15*(198-207).

Springer DOI
**1511**

BibRef

*Lam, M.[Michael]*,
*Doppa, J.R.[Janardhan Rao]*,
*Todorovic, S.[Sinisa]*,
*Dietterich, T.G.[Thomas G.]*,

**HC-search for structured prediction in computer vision**,

*CVPR15*(4923-4932)

IEEE DOI
**1510**

works for language, try for vision.
BibRef

*Roy, A.[Anirban]*,
*Todorovic, S.[Sinisa]*,

**Scene Labeling Using Beam Search under Mutex Constraints**,

*CVPR14*(1178-1185)

IEEE DOI
**1409**

Beam Search; Mutex Constraints; Scene Labeling
BibRef

*Sun, M.[Min]*,
*Huang, W.[Wan]*,
*Savarese, S.[Silvio]*,

**Find the Best Path:
An Efficient and Accurate Classifier for Image Hierarchies**,

*ICCV13*(265-272)

IEEE DOI
**1403**

branch-and-bound
BibRef

*Mudaliar, D.N.[Devasenathipathi N.]*,
*Modi, N.K.[Nilesh K.]*,

**Unraveling Travelling Salesman Problem by genetic algorithm using
m-crossover operator**,

*ICSIPR13*(127-130).

IEEE DOI
**1304**

BibRef

*Nguyen, H.T.[Hoang Thanh]*,
*Bhanu, B.[Bir]*,

**Zombie Survival Optimization: A swarm intelligence algorithm inspired
by zombie foraging**,

*ICPR12*(987-990).

WWW Link.
**1302**

Search optimization
BibRef

*Kappes, J.H.[Jörg Hendrik]*,
*Beier, T.[Thorsten]*,
*Schnörr, C.[Christoph]*,

**MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by
Fusion Moves**,

*GMCV14*(469-484).

Springer DOI
**1504**

BibRef

*Andres, B.[Bjoern]*,
*Kappes, J.H.[Jörg H.]*,
*Beier, T.[Thorsten]*,
*Köthe, U.[Ullrich]*,
*Hamprecht, F.A.[Fred A.]*,

**The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete
Graphical Models**,

*ECCV12*(VII: 154-166).

Springer DOI
**1210**

BibRef

*Zielinski, B.[Bartlomiej]*,
*Iwanowski, M.[Marcin]*,

**Comparing Image Objects Using Tree-Based Approach**,

*ICCVG12*(702-709).

Springer DOI
**1210**

BibRef

*Vallotton, P.*,
*Lovell, D.*,
*Newman, J.*,

**An Observation about Circular Shortest Paths:
Dealing with Additional Constraints Using Branch and Bound**,

*DICTA11*(513-517).

IEEE DOI
**1205**

BibRef

*Chakrabarti, P.P.[Partha Pratim]*,
*Aine, S.[Sandip]*,

**New Approaches to Design and Control of Time Limited Search Algorithms**,

*PReMI09*(1-6).

Springer DOI
**0912**

BibRef

*Zhu, W.X.[Wei-Xing]*,
*Chen, X.Y.[Xian-Yong]*,
*Li, X.C.[Xin-Cheng]*,

**A New Search Algorithm Based on Muti-Octagon-Grid**,

*CISP09*(1-5).

IEEE DOI
**0910**

BibRef

*Dwyer, T.[Tim]*,
*Hurst, N.[Nathan]*,
*Merrick, D.[Damian]*,

**A Fast and Simple Heuristic for Metro Map Path Simplification**,

*ISVC08*(II: 22-30).

Springer DOI
**0812**

Shortest path.
BibRef

*Boffy, A.*,
*Tsin, Y.*,
*Genc, Y.*,

**Real-Time Feature Matching using Adaptive and Spatially Distributed
Classification Trees**,

*BMVC06*(II:529).

PDF File.
**0609**

BibRef

*Serratosa, F.[Francesc]*,
*Sanromā, G.[Gerard]*,
*Sanfeliu, A.[Alberto]*,

**A New Algorithm to Compute the Distance Between Multi-dimensional
Histograms**,

*CIARP07*(115-123).

Springer DOI
**0711**

BibRef

*Serratosa, F.[Francesc]*,
*Sanromā, G.[Gerard]*,

**An Efficient Distance Between Multi-dimensional Histograms for
Comparing Images**,

*SSPR06*(412-421).

Springer DOI
**0608**

BibRef

*Serratosa, F.[Francesc]*,
*Sanfeliu, A.[Alberto]*,

**Vision-Based Robot Positioning by an Exact Distance Between Histograms**,

*ICPR06*(II: 849-852).

IEEE DOI
**0609**

BibRef

And:

**A Fast and Exact Modulo-Distance Between Histograms**,

*SSPR06*(394-402).

Springer DOI
**0608**

To determine if the image is familiar.
BibRef

*Serratosa, F.[Francesc]*,
*Sanfeliu, A.[Alberto]*,

**Matching Attributed Graphs:
2nd-Order Probabilities for Pruning the Search Tree**,

*IbPRIA05*(II:131).

Springer DOI
**0509**

BibRef

*Wahl, E.[Eric]*,
*Hirzinger, G.[Gerd]*,

**A Method for Fast Search of Variable Regions on Dynamic 3D Point Clouds**,

*DAGM05*(208).

Springer DOI
**0509**

BibRef

*Thayananthan, A.*,
*Stenger, B.*,
*Torr, P.H.S.*,
*Cipolla, R.*,

**Learning a Kinematic Prior for Tree-Based Filtering**,

*BMVC03*(xx-yy).

HTML Version.
**0409**

Tree based evaluation for tracking.
BibRef

*Stenger, B.*,
*Thayananthan, A.*,
*Torr, P.H.S.*,
*Cipolla, R.*,

**Filtering using a tree-based estimator**,

*ICCV03*(1063-1070).

IEEE DOI
**0311**

BibRef

*Huber, D.F.[Daniel F.]*,
*Hebert, M.[Martial]*,

**3D Modeling Using a Statistical Sensor Model and Stochastic Search**,

*CVPR03*(I: 858-865).

IEEE DOI

HTML Version.
**0307**

BibRef

And:
*CREST03*(125-126).
**0309**

BibRef

*Kovtun, I.[Ivan]*,

**Partial Optimal Labeling Search for a NP-Hard Subclass of (max,+)
Problems**,

*DAGM03*(402-409).

Springer DOI
**0310**

*Award, GCPR, HM*.
BibRef

*Hao, H.W.[Hong-Wei]*,
*Liu, C.L.[Cheng-Lin]*,
*Sako, H.*,

**Comparison of genetic algorithm and sequential search methods for
classifier subset selection**,

*ICDAR03*(765-769).

IEEE DOI
**0311**

BibRef

*Tabibi, O.D.[Omid David]*,
*Netanyahu, N.S.[Nathan S.]*,

**Verified Null-move Pruning**,

*UMD*-- TR4406, October 2002.

WWW Link.

WWW Link.
BibRef
**0210**

*Jepson, A.D.[Allan D.]*,
*Mann, R.[Richard]*,

**Qualitative Probabilities for Image Interpretation**,

*ICCV99*(1123-1130).

IEEE DOI Probabilistic pruning of search tree.
BibRef
**9900**

*Greenspan, M.A.[Michael A.]*,

**The Sample Tree:
A Sequential Hypothesis Testing Approach to 3D Object Recognition**,

*CVPR98*(772-779).

IEEE DOI
BibRef
**9800**

*Chung, H.Y.*,
*Cheung, P.Y.S.*,
*Yung, N.H.C.*,

**Adaptive search center non-linear three step search**,

*ICIP98*(II: 191-194).

IEEE DOI
**9810**

BibRef

*Commike, A.Y.*,
*Hull, J.J.*,

**Syntactic pattern classification by branch and bound search**,

*CVPR91*(432-437).

IEEE DOI
**0403**

BibRef

*Tanimoto, S.L.*,

**Machine Vision as State-Space Search**,

*MVAAS88*(XX-YY).
*Search Techniques*. Model vision as a search. Describe search techniques.
BibRef
**8800**

*Breuel, T.M.[Thomas M.]*,

**Geometric Aspects of Visual Object Recognition**,

*MIT AI-TR*-1374, May 1992.
BibRef
**9205**
*Ph.D.*thesis, MIT, 1992.

WWW Link.
BibRef

*Breuel, T.M.*,

**Higher-Order Statistics in Object Recognition**,

*CVPR93*(707-708).

IEEE DOI
BibRef
**9300**

*Breuel, T.M.*,

**Fast Recognition Using Adaptive Subdivisions of Transformation Space**,

*CVPR92*(445-451).

IEEE DOI This algorithm is faster than the alignment and Hough methods.
BibRef
**9200**

*Breuel, T.M.*,

**Model Based Recognition Using Pruned Correspondence Search**,

*CVPR91*(257-262).

IEEE DOI Reduce potentially exponential time algorithms to polynomial time by
requiring the matching of features to convex regions.
BibRef
**9100**

*Breuel, T.M.[Thomas M.]*,

**An Efficient Correspondence Based Algorithm for 2D and 3D
Model Based Recognition**,

*MIT AI Memo*-1259, October 1990.
BibRef
**9010**

*Breuel, T.M.[Thomas M.]*,

**Indexing for Visual Recognition from a Large Model Base**,

*MIT AI Memo*-1108, August 1990.

WWW Link.
BibRef
**9008**

*Breuel, T.M.*,

**Adaptive Model Base Indexing**,

*DARPA89*(805-814).
BibRef
**8900**

*Blostein, S.D.*,
*Huang, T.S.*,

**A Tree Search Algorithm for Target Detection in Image Sequences**,

*CVPR88*(690-695).

IEEE DOI
BibRef
**8800**

*Brailovsky, V.L.*,

**A probabilistic estimate of clustering**,

*ICPR90*(I: 953-956).

IEEE DOI
**9006**

BibRef

Earlier:

**On use of predictive probabilistic estimates for selecting best
decision rules in the course of a search**,

*CVPR88*(469-475).

IEEE DOI
**0403**

BibRef

*Gennery, D.B.*,

**A Feature-Based Scene Matcher**,

*IJCAI81*(667-673), (JPL).
Match 2 scene descriptions - set of feature vectors, differ by
unknown transformation. Method: search by sequentially matching
features of one scene to those of the other scene. Computer
transformations and probability of match - use these to prune tree.
Search: choose of possible match for one element (try all), choose
a consistent match for the next element, etc. Standard search
problems. Examples are on small numbers.
BibRef
**8100**

*Smith, D.R.[David R.]*,

**Search Strategies for the ARGOS Image Understanding System**,

*DARPAN79*(42-46).
Extension of the ARGOS system.
BibRef
**7900**

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in

Tabu Search .

Last update:Sep 15, 2024 at 16:30:49