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Improving Object Detection Performance with Genetic Programming
Mengjie Zhang International Journal on Artificial Intelligence Tools 16(5):849--873 (October 2007)
to algorithms, fitness function, genetic learning, networks neural object program programming, recognition, size, target two-phase by brazovayeye and 1 other user on Jun 19, 2008, 5:46 PM
DOI | BibTeX (0)
A Domain-independent Window approach to Multiclass Object Detection using Genetic Programming
Mengjie Zhang, Victor B. Ciesielski, and Peter Andreae EURASIP Journal on Applied Signal Processing 2003(8):841--859 (July 2003)Special Issue on Genetic and Evolutionary Computation for Signal Processing and Image Analysis .
to algorithms, computer detection, genetic learning, machine networks, neural object programming, recognition, target vision by brazovayeye and 1 other user on Jun 19, 2008, 5:46 PM
URL | DOI | BibTeX (0)
Genetic Programming for Multiple Class Object Detection
Mengjie Zhang, and Victor Ciesielski 12th Australian Joint Conference on Artificial Intelligence, volume 1747 of LNAI, page 180--192. Sydney, Australia, Springer-Verlag, (June 1999)
to Machine Neural Vision algorithms, genetic learning, networks, programming, by brazovayeye and 1 other user on Jun 19, 2008, 5:46 PM
URL | BibTeX (0)
Modelling rainfall-runoff using genetic programming
P. A. Whigham, and P. F. Crapper Mathematical and Computer Modelling 33(6-7):707--721 (2001)
to Chlorophyll-a Machine Time algorithms, genetic learning, modelling modelling, programming, series by brazovayeye on Jun 19, 2008, 5:46 PM
URL | DOI | BibTeX (0)
Induction of a marsupial density model using genetic programming and spatial relationships
P. A. Whigham Ecological Modelling 131(2-3):299--317 (2000)
to Habitat Machine Spatial algorithms, genetic learning, patterns, prediction programming, by brazovayeye on Jun 19, 2008, 5:46 PM
URL | DOI | BibTeX (0)
A discipline of evolutionary programming
Paul Vitanyi Theoretical Computer Science 241(1--2):3--23 (April 2002)
to Algorithms, Artificial Complexity, Computational Computing, Data Evolutionary Intelligence, Learning, Multiagent Neural Structures Systems algorithms, and genetic programming, by brazovayeye on Jun 19, 2008, 5:46 PM
URL | BibTeX (0)
Evolving rule-based systems in two medical domains using genetic programming
Athanasios Tsakonas, Georgios Dounias, Jan Jantzen, Hubertus Axer, Beth Bjerregaard, and Diedrich Graf von Keyserlingk Artificial Intelligence in Medicine 32(3):195--216 (November 2004)
to Aphasia, GP, Genetic-fuzzy Grammar Hybrid Inductive Medical Pap-smear algorithms, decision driven genetic intelligence, learning, machine making, programming, systems, test by brazovayeye and 2 other users on Jun 19, 2008, 5:46 PM
URL | DOI | BibTeX (0)
Faster Genetic Programming based on Local Gradient Search of Numeric Leaf Values
Alexander Topchy, and William F. Punch Proceedings of the Genetic and Evolutionary Computation Conference GECCO-2001, page 155--162. San Francisco, California, USA, Morgan Kaufmann, (July 2001)
to Baldwin Lamarckian algorithmic, algorithms, differentiation, effect, genetic gradient learning, optimization, programming, regression symbolic by brazovayeye on Jun 19, 2008, 5:46 PM
URL | BibTeX (0)
GECCO 2007: Proceedings of the 9th annual conference on Genetic and evolutionary computation
Dirk Thierens, Hans-Georg Beyer, Josh Bongard, Jurgen Branke, John Andrew Clark, Dave Cliff, Clare Bates Congdon, Kalyanmoy Deb, Benjamin Doerr, Tim Kovacs, Sanjeev Kumar, Julian F. Miller, Jason Moore, Frank Neumann, Martin Pelikan, Riccardo Poli, Kumara Sastry, Kenneth Owen Stanley, Thomas Stutzle, Richard A Watson, and Ingo Wegener (Eds.). London, UK, ACM Press, (July 2007)
to Adaptive Algorithms, Ant Applications, Artificial Behaviour, Biological Coevolution, Colony Developmental Distribution Engineering Estimation Evolution Evolutionary Evolvable Formal Generative Genetics-Based Hardware, Immune Intelligence, Learning, Life, Machine Multiobjective Optimisation, Programming, Real-World Robotics, Search-Based Software Strategies, Swarm Systems, Theory, algorithms, and genetic of programming, by brazovayeye on Jun 19, 2008, 5:46 PM
BibTeX (0)
Learning Concept Descriptions with Typed Evolutionary Programming
Claire J. Thie, and Christophe Giraud-Carrier IEEE Transactions on Knowledge and Data Engineering 17(12):1664--1677 (2005)
to Concept STGP, algorithms, evolutionary genetic learning, programming programming, typed by brazovayeye and 1 other user on Jun 19, 2008, 5:46 PM
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Internal reinforcement in a connectionist genetic programming approach
Astro Teller, and Manuela Veloso Artificial Intelligence 120(2):165--198 (July 2000)
to Bucket Evolutionary Internal Machine Neural Signal algorithms, brigade computation, genetic learning, programming, reinforcement, understanding, by brazovayeye and 1 other user on Jun 19, 2008, 5:46 PM
URL | DOI | BibTeX (0)
When lisp is faster than C
Borge Svingen GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, 1, page 957--958. Seattle, Washington, USA, ACM Press, (August 2006)
to Artificial C, Experimentation, Intelligence, Learning, Performance Performance, Poster, algorithms, genetic implementation, languages, lisp, programming: by brazovayeye and 1 other user on Jun 19, 2008, 5:46 PM
URL | DOI | BibTeX (0)
Automated Discovery of Numerical Approximation Formulae Via Genetic Programming
Matthew J. Streeter Computer Science, Worcester Polytechnic Institute, MA, USA, (May 2001)
to algorithms, approximations, artificial genetic intelligence learning, machine programming, by brazovayeye on Jun 19, 2008, 5:46 PM
URL | BibTeX (0)
Evolutionary Principles in Self-Referential Learning. On Learning now to Learn: The Meta-Meta-Meta...-Hook
Jurgen Schmidhuber Technische Universitat Munchen, Germany, Diploma Thesis, (February 1988)
to EURISKO, PSALM, SALM, algorithm, algorithms, associative brigade, bucket evolution, fractals genetic genetical introsepection, learning, meta, nets, neuronal programming self-reference, by brazovayeye on Jun 19, 2008, 5:46 PM
URL | BibTeX (0)
Probabilistic Model Building and Competent Genetic Programming
Kumara Sastry, and David E. Goldberg Genetic Programming Theory and Practise, chapter 13, Kluwer, (2003)
to Competent Extended Linkage Probabilistic adaptation, algorithm algorithms, building, compact genetic learning, model program, programming, by brazovayeye and 1 other user on Jun 19, 2008, 5:46 PM
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Probabilistic Incremental Program Evolution: Stochastic Search Through Program Space
R. P. Salustowicz, and J. Schmidhuber Machine Learning: ECML-97, volume 1224 of Lecture Notes in Artificial Intelligence, page 213--220. Springer-Verlag, (1997)
to Incremental Learning, Population-Based Program Search Stochastic algorithms, genetic programming, by brazovayeye and 3 other users on Jun 19, 2008, 5:46 PM
URL | BibTeX (0)
Learning Team Strategies: Soccer Case Studies
R. P. Sałustowicz, M. A. Wiering, and J. Schmidhuber Machine Learning 33(2-3):263--282 (December 1998)
to PIPE, TD-Q coevolution evaluation evolution, functions, incremental learning, multiagent probabilistic program reinforcement soccer, by brazovayeye and 3 other users on Jun 19, 2008, 5:46 PM
URL | BibTeX (0)
Probabilistic Incremental Program Evolution
R. P. Salustowicz, and J. Schmidhuber Evolutionary Computation 5(2):123--141 (1997)
to Evolution, Incremental Learning, Population-Based Program algorithms, environments genetic languages, observable partially probabilistic program programming programming, search, stochastic by brazovayeye and 4 other users on Jun 19, 2008, 5:46 PM
URL | DOI | BibTeX (0)
Scaling Up Inductive Logic Programming: An Evolutionary Wrapper Approach
Philip G. K. Reiser, and Patricia J. Riddle Applied Intelligence 15(3):181--197 (November 2001)Special Issue: Simulated Evolution and Learning .
to ILP algorithms, evolutionary genetic inductive learning, logic machine programming, sampling, by brazovayeye and 1 other user on Jun 19, 2008, 5:46 PM
URL | DOI | BibTeX (0)
High Fidelity Approximation of Slow Simulators Using Machine Learning for Real-time Simulation/Optimization
Sudip Regmi, Larry M. Deschaine, and Sharad R. Regmi 2004 Business and Industry Symposium, Washington, DC, USA, (April 2004)
to Learning, Machine Optimisation Simulation, algorithms, genetic programming, by brazovayeye on Jun 19, 2008, 5:46 PM
URL | BibTeX (0)

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