Color is a powerful feature for image analysis but it is usually not used in image classification schemes. We propose a method to combine fuzzy color information with the result obtained from a One-Versus-All classifi...
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ISBN:
(纸本)9781509060351
Color is a powerful feature for image analysis but it is usually not used in image classification schemes. We propose a method to combine fuzzy color information with the result obtained from a One-Versus-All classifier (OVA) trained with Bag-of-features. This method consists in weighting the outputs of the OVA classifier based on the distances between the new image to be classified and the classes. Experimental results show that our approach improves OVA classifier performance.
A new general multi-objective optimization heuristic algorithm, suitable for being applied to continuous multi-objective optimization problems is proposed. It deals with the problem at hand in a fast and efficient way...
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Advanced parallel Multi-Objective Evolutionary Algorithms (MOEA) have been used in order to solve a wide array of problems, including the planning of greenhouse crops. This paper shows the application of MOEA using th...
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The two-dimensional bin-packing problem (2D-BPP) with rotations is an important optimization problem which has a large number of practical applications. It consists of the non-overlapping placement of a set of rectang...
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Multicast peer-to-peer overlays are being progressively adopted in commercial platforms in spite of some childhood problems. One of the major issues that need further development is key distribution and conditional ac...
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In this work, a parallel version of the evolutionary algorithm called UEGO (Universal Evolutionary Global Optimizer) has been implemented and evaluated on shared memory architectures. It is based on a threaded program...
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Interval Global Optimization based on Branch and Bound (B&B) technique is a standard for searching an optimal solution in the scope of continuous and discrete Global Optimization. It iteratively creates a search t...
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In this paper, we present a tool devised for the automatic design and optimization of bioinspired visual processing models using reconfigurable hardware. We have focused on the simulation and optimization characterist...
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Electron microscope tomography allows determination of the 3D structure of biological specimens, which is critical to understanding their function. Prior to the 3D reconstruction procedure, the images taken from the m...
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Electron microscope tomography allows determination of the 3D structure of biological specimens, which is critical to understanding their function. Prior to the 3D reconstruction procedure, the images taken from the microscope have to be properly aligned. Traditional alignment methods in this field are based on a phase residual function to be minimized by inefficient exhaustive search procedures. This work addresses this minimization problem from a global optimization perspective. UEGO, an evolutionary multimodal optimization algorithm, has been applied and evaluated for the task of image alignment in this field. UEGO has turned out to be a promising technique alternative to the standard methodology. The alignments found out by UEGO show high levels of accuracy, while reducing the number of function evaluations by a significant factor with respect to the standard method.
This work presents an initiative to teach the basis of fault tolerance in digital systems design in undergraduate and graduate courses in electrical and computer engineering. The approach is based on a library of char...
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