João F. Mari

Learn More
Recently, we are attending to a huge evolution on the development of high performance computing platforms. Among these platforms, the GPU (Graphics Processing Units) stimulated by game industries, constantly demanding more graphical processing power, evolved from a simple graphical card to a general purpose computation parallel data processing device. This(More)
This work presents an implementation of neocognitron neural network, using a high performance computing architecture based on GPU (graphics processing unit). Neocognitron is an artificial neural network, proposed by Fukushima and collaborators, constituted of several hierarchical stages of neuron layers, organized in two-dimensional matrices called cellular(More)
This ongoing project describes neural network applications for helping musical composition using as inspiration the natural landscape contours. We propose supervised and unsupervised learning approaches, by using Back-Propagation-Through-Time (BPTT) and Self Organizing Maps (SOM) neural networks. In the supervised learning, the network learns certain(More)
The reconstruction of a three-dimensional surface from a set of unorganized points is a fundamental process in a lot of applications, including laser range scanners, medical imaging, and others. This work presents a modified version of the Neural Meshes algorithm for surface reconstruction from point cloud, called Neural Meshes with Edge Swap, or Neural(More)
Microelectrode Arrays (MEA) are devices for long term electrophysiological recording of extracellular spontaneous or evocated activities on in vitro neuron culture. This work proposes and develops a framework for quantitative and morphological analysis of neuron cultures on MEAs, by processing their corresponding images, acquired by fluorescence microscopy.(More)
  • 1