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aracaju,
brazil
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Ingressou em julho 11, 2018
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Helton L.
@heltondanilo
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aracaju,
brazil
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Lead Software Engineer at LumenGames
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Experiência
Lead Software Engineer / Game Developer
jul. 2016 - Atual
Half of my time is making sure everyone is working as they should, with proper documentation and tasks clear, the other half I nail the most risks area of the code, some times coding my self, some times describing technical documents that can lead to a lean development of the features. I also plan the big changes in the software architecture and cloud architecture. Currently working on the next F2P big hit on simulation category.
Software Engineer / Game Developer
jul. 2015 - jul. 2016 (1 ano)
Started as software engineer for c#, didn't have much experience in Unity 3D, but since I had experience with other engines before(Panda3D, XNA, SDL), I was able to handle Unity 3D properly in a month. Started a F2P mobile game from scratch in the new team, and that mobile game was making 400k$/month two years after.
Student Researcher
jun. 2013 - jun. 2016 (3 anos)
Worked in the Image Processing, parallelization, heterogeneous computing, and fast computing. Developed the framework VisionGL that is cappable of doing image operations up to 10 thousand times faster than the other open source options. Supports multidimentional image and CPU/GPU processing. Also can read and write medical images.
Educação
Bachelor in computer science
(6 anos)
Qualificações
Featured Research in 25º EIC
Universidade Federal de Sergipe
2016
One of the researches that I did when majoring was awarded with honorable mention, due to the results and impact. In the research, I developed a framework 1000 to 10000 times faster than the current open source available in the market for image processing specially in the medical field
Publicações
Blood vessels extraction using Fuzzy Mathematical Morphology
IEEE International Conference on Acoustics, Speech and Signal Processing, 2017
Blood vessel extraction from retinography images is useful for detection of many retinopathies. In this paper we propose a way to improve blood vessel detection by use of Fuzzy Mathematical Morphology (FMM) operators. The proposed pipeline, although simple, was found to have the highest accuracy on the STARE dataset, and second highest on the DRIVE dataset. We also present a parallel implementation of the FMM operators, in OpenCL, up to about 500 times faster than their counterpart in C++.
Fast multidimensional image processing with OpenCL
IEEE International Conference on Image Processing, 2016
The objective of this work is to augment VisionGL by adding multidimensional image processing support with OpenCL for high performance through use of GPUs. Benchmarking experiments were ran with window and point operations to compare Python, MATLAB and VisionGL when processing 1D to 5D images. As a result, speedups of up to 10000 times faster.
Fast 2d and 3d image processing with OpenCL
IEEE International Conference on Image Processing, 2015
The libraries that support OpenCL on GPU usually they don't support processing 3D images. The reason is that it is not as simple as programming CPUs, and many API calls are needed to prepare the environment before calling the shader. In this article we describe a library with a code generator that, using few directives merged in a shader code, generates a code with all the OpenCL API calls needed before calling the shader, simplifying, thus, the maintenance of an image processing library.
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