Carrión-Ojeda, D., Martínez-Arias, P., Fonseca-Delgado, R., & Pineda, I. (2021). EBAPy: A Python framework for analyzing the factors that have an influence in the performance of EEG-based applications. Software Impacts, 100062. https://doi.org/10.1016/J.SIMPA.2021.100062
J. Nkechinyer, E. Morocho-Cayamcela, W. Lim, "CGDNet: Efficient Hybrid Deep Learning Model for Robust Automatic Modulation Recognition", Feb. 2021
D. Carrión-Ojeda, R. Fonseca-Delgado, and I. Pineda, “Analysis of factors that influence the performance of biometric systems based on EEG signals,” Expert Syst. Appl., vol. 165, p. 113967, Mar. 2021.
O. Chang, F. A. Gonzales-Zubiate, L. Zhinin-Vera, R. Valencia-Ramos, I. Pineda, and A. Diaz-barrios, “A Protein Folding Robot Driven by a Self-taught Agent A Protein Folding Robot Driven by a Self-taught Agent,” BioSystems, 2020. (In Press)
I. Pineda, C. Zhunio, F. Camacho, and R. Fonseca-Delgado, “RAPL : A Domain Specific Language for Resource Allocation of Indivisible Goods,” in Communications in Computer and Information Science, 2020, pp. 1–14.
R. Valencia-Ramos, L. Zhinin-Vera, O. Chang, and I. Pineda, “E-Move : Domain Specific Language for People with Movement Disorders,” in Communications in Computer and Information Science, 2020, vol. 1, pp. 1–8.
I. Pineda, D. Arellano, and R. Chachalo, “Analysis of Essentially Non-oscillatory Numerical Techniques for the Computation of the Level Set Method,” in Applied Technologies, 2020, pp. 395–408.
O. Guarnizo and I. Pineda, “Three Dimensional Adaptive Path Planning Simulation Based On Ant Colony Optimization Algorithm,” in Latin American Conference on Computational Intelligence LA-CCI, 2019.
I. Pineda, N. Alam MD, and O. Gwun, “Calyx and Stem Discrimination for Apple Quality Control Using Hyperspectral Imaging,” in 4th International Conference on Technology Trends, 2018, pp. 274–287.
N. Alam, I. Pineda, J. G. Lim, and O. Gwun, “Apple Defects Detection Using Principal Component Features of Multispectral Reflectance Imaging,” Sci. Adv. Mater., vol. 10, pp. 1051–1062, 2018.
I. Pineda, “An Enhanced Level Set Method and Its Application to the Simulation of Fluids and Leaves,” Chonbuk National University, 2018.
S. Jeong, I. Pineda, and O. Gwun, “Optimization of the Hash Table Parameters to Store the Narrow Band Level Set Method,” in ISITC 2017 International Symposium on Information Technology Convergence, 2017.
I. Pineda and O. Gwun, “Level Set Method Simulation of Leaves: Comparative Evaluation of Active Contour and Variational Level Set Method,” in ISITC 2017 International Symposium on Information Technology Convergence, 2017.
I. Pineda and O. Gwun, “Tobacco Leaf Area Growth Simulation with the Variational Level Set Method,” in Third International Conference on Electronics and Software Science (ICESS2017), 2017, pp. 171–175.
I. Pineda and O. Gwun, “Leaf Modeling and Growth Process Simulation Using the Level Set Method,” IEEE Access, vol. 5, pp. 15948–15959, 2017.
I. Pineda and O. Gwun, “Lagrangian Particles Sampling for Eulerian Level Set Simulation,” in ISITC 2016 International Symposium on Information Technology Convergence, 2016, pp. 244–249.
I. Pineda, “Level Set Based Fluid Simulation Featuring Surface Tension,” Chonbuk National University, 2015.
I. Pineda and O. Gwun, “Level Set Advection of Free Fluid Surface Modified by Surface Tension,” Smart Media J., vol. 4, no. 2, pp. 9–16, 2015.
I. Pineda and O. Gwun, “Surface Tension Approximation in Semi-Lagrangian Level Set Based Fluid Simulations for Computer Graphics,” in CGMIP 2014 The International Conference on Computer Graphics, Multimedia and Image Processing, 2014, pp. 49–55.
I. Pineda and O. Gwun, “Level Set Based Large-Scale Fluid Simulations Using Surface Tension Approximation For Detail Increment,” in ISITC 2014 International Symposium on Information Technology Convergence, 2014, pp. 436–439.
Conference Papers & Posters
Simulation Based on the Navier Stokes Equations Using Finite Differences
Numerical Techniques for a Didactic Implementation of the Level Set Method
Visualization Techniques for Distance Functions: Comparison Between VTK and OpenGL
Path Planning Simulation in Controlled Environments using the Ants Colony Optimization Algorithm