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In this paper we propose a robust and fully automated lumbar herniation diagnosis system based on clinical MRI data which will not only aid a radiologist to make a decision with increased confidence, but will also reduce the time needed to analyze each case. Our method is based on three steps : 1) We automatically label the five lumbar intervertebral discs in a sagittal MRI slice using a probabilistic...
Image registration is considered one of the most fundamental and crucial pre-processing tasks in digital imaging. This paper describes a fast multimodal automatic image registration algorithm that handles the alignment of IR and visible images. A multiresolution approach based on dual tree-complex wavelet transform is employed to speed up the process. At the coarsest level, an accurate registration...
Multiplication is at the core of many data processing tasks and saving power at the multiplication level can significantly impact the lifetime of a wireless sensor network. This paper introduces a novel light-weight low-power multiplication algorithm which is tailored for sensor nodes featuring low-end microcontrollers. These microcontrollers might have no hardware multiplier, or feature a fixed-point...
Object detection is receiving a growing attention with the emergence of surveillance systems. This paper presents a hybrid adaptive scheme based on selective Gaussian modeling for detecting objects in complex outdoor scenes with gradual illumination changes and dense, moving background objects like swinging tree branches. The proposed technique combines simple frame difference (FD), simple adaptive...
Social insects like ants, bees deposit pheromone (a type of chemical) in order to communicate between the members of their community. Pheromone, that causes clumping behavior in a species and brings individuals into a closer proximity, is called aggregation pheromone. This article presents a new algorithm (called, APC) for pattern classification based on the property of aggregation pheromone found...
This paper describes a method for improving the final accuracy and the convergence speed of Particle Swarm Optimization (PSO) by adapting its inertia factor in the velocity updating equation and also by adding a new coefficient to the position updating equation. These modifications do not impose any serious requirements on the basic algorithm in terms of the number of Function Evaluations (FEs). The...
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