Iris Fermin

Learn More
The seeded region growing (SRG) algorithm is a fast robust parameter-free method for segmenting intensity images given initial seed locations for each region. The requirement of predetermined seeds means that the model cannot operate fully autonomously. In this paper, we demonstrate a novel region growing variant of the pulse-coupled neural network (PCNN),(More)
In this paper, we report an initial design of humanoid head platform for RoboCup humanoid challenge. While many research in RoboCup humanoid challenge naturally focus on walking and running behaviors, we focus on perception and high-level behavior issues using an upper-torso humanoid. We have designed an head/neck part of the humanoid with aesthetic design,(More)
— The EENCL algorithm [1] has been proposed as a method for designing neural network ensembles for classification tasks, combining global evolution with a local search based on gradient descent. Two mechanisms encourage diversity: Negative Correlation Learning (NCL) and implicit fitness sharing. In order to better understand the success of EENCL, this work(More)
The EENCL algorithm [1] automatically designs neural network ensembles for classification, combining global evolution with local search based on gradient descent. Two mechanisms encourage diversity: Negative Correlation Learning (NCL) and implicit fitness sharing. This paper analyses EENCL, finding that NCL is not an essential component of the algorithm,(More)
—In many situations it is important to deliver information to personnel as they perform a mission. We consider such a specialized content distribution application. When a mission is created, for example when an alarm for a fire is reported, data is pushed to storage nodes at the mission site where it may be retrieved locally by responding personnel (e.g.,(More)