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This paper proposes a generalized Bayesian strategy for relevance feedback in Region-Based image retrieval The presented feedback technique is based on Bayesian learning method and incorporates a time-varying user model . We give the user model with two terms: a target query and a user conception. The user conception is aimed to learn a parameter set to determine the time-varying matching criterion...
This paper introduces a modified PSO, gradient particle swarm optimizer (GPSO), for geometric constraint solving. GPSO combines the merits of global search of the PSO and the sheer convergence capacity of gradient algorithm, the most prominent iterative method for linear equations. GPSO uses PSO to search the area where the best solution may exist in the whole space, and then performs fine searching...
To solve the constraint multi-solution problem, the constraints are separated to two sets, the original constraint set and the additional constraint set. First, the solver finds out multiple solutions. Then genetic algorithm and ant algorithm are combined in the process of searching optimal solution. We adopt genetic algorithm in the former process to produce the initiatory distribution of information...
In this paper, a new optimization method, Organizational Evolutionary Algorithm (OEA), is proposed, in which a population is made of organizations and whose evolution is led by three organizational evolutionary operators, i.e. the splitting operator, the merging operator and the cooperating operator; the splitting operator controls the size of organizations and make part of organizations enter into...
Geometric constraint problem can be transformed to an optimization problem which the objective function and constraints are non-convex functions. In this paper an evolutionary algorithm based on ant colony optimization algorithm and the immune system model is proposed to provide solution to the geometric constraints problem. In the new algorithm, affinity calculation process and pheromone trail lying...
In this paper, we propose a hybrid algorithm -(parallel search algorithm) to solve geometric constraint problems. First, particle swarm optimization is employed to gain parallelization while solution diversity is maintained. Second, simplex method reduces the number of infeasible solutions while solution quality is improved with an operation order search. Performance results on geometric constraint...
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