Note: You can find my entire and updated list of publications in my GOOGLE SCHOLAR PROFILE

Publications in international journals

  1. Oliva, D., Esquivel-Torres, S., Hinojosa, S., Pérez-Cisneros, M., Osuna-Enciso, V., Ortega-Sánchez, N., … & Heidari, A. A. (2021). Opposition-based moth swarm algorithm. Expert Systems with Applications, 184, 115481.
  2. Singh, S., Mittal, N., Thakur, D., Singh, H., Oliva, D., & Demin, A. (2021). Nature and Biologically Inspired Image Segmentation Techniques. Archives of Computational Methods in Engineering, 1-28.
  3. Abd Elaziz, M., Mohammadi, D., Oliva, D., & Salimifard, K. (2021). Quantum marine predators algorithm for addressing multilevel image segmentation. Applied Soft Computing, 107598.
  4. Ayaz, H., Rodríguez-Esparza, E., Ahmad, M., Oliva, D., Pérez-Cisneros, M., & Sarkar, R. (2021). Classification of Apple Disease Based on Non-Linear Deep Features. Applied Sciences, 11(14), 6422.
  5. A. A. Juan, P. Keenan, R. Martí, S. McGarraghy, J. Panadero, P. Carroll, D. Oliva. A review of the role of heuristics in stochastic optimisation: from metaheuristics to learnheuristics.  Annals of Operations Research (2021), 1-31.
  6. A. M. Anter, D. Oliva, A. Thakare, Z Zhang. AFCM-LSMA: New Intelligent Model based on Lévy Slime Mould Algorithm and Adaptive Fuzzy C-means for Identification of COVID-19 Infection from Chest X-ray Images. Advanced Engineering Informatics (2021), 101317.
  7. P. Agrawal, T. Ganesh, D. Oliva, A. W. Mohamed. S-shaped and V-shaped gaining-sharing knowledge-based algorithm for feature selection. Applied Intelligence (2021), 1-32.
  8. M. Abd Elaziz, A. H. Elsheikh, D. Oliva, L. Abualigah, S. Lu, A. A. Ewees. Advanced Metaheuristic Techniques for Mechanical Design Problems. Archives of Computational Methods in Engineering (2021) , 1-22.
  9. M. Scoczynski, M. Delgado, R. Lüders, D. Oliva, M. Wagner, I. Sung, M. El Yafrani. Saving computational budget in Bayesian network-based evolutionary algorithms. Natural Computing (2021), 1-16.
  10. O. Ramos-Soto, E.Rodríguez-Esparza, S. E. Balderas-Mata, D. Oliva, A. E. Hassanien, R. K. Meleppat, R. J. Zawadzki. An efficient retinal blood vessel segmentation in eye fundus images by using optimized top-hat and homomorphic filtering. Computer Methods and Programs in Biomedicine, (2021) 201, 105949.
  11. E. H. Houssein, B. E. D. Helmy, D. Oliva, A. A. Elngar, H. Shaban. A novel Black Widow Optimization algorithm for multilevel thresholding image segmentation. Expert Systems with Applications, (2020) 114159.
  12. Dong Zhao, Lei Liu, Fanhua Yu, Ali Asghar Heidari, Mingjing Wang, Diego Oliva, Khan Muhammad, Huiling Chen,(2020). Ant colony optimization with horizontal and vertical crossover search: Fundamental visions for multi-threshold image segmentation. Expert Systems with Applications, (2020) 114122.
  13. N. Akbarpour, A. Salehi-Amiri, M. Hajiaghaei-Keshteli, D. Oliva. An innovative waste management system in a smart city under stochastic optimization using vehicle routing problem. Soft Computing, (2021) 1-21.
  14. A. A. Ismaeel, E. H. Houssein, D. Oliva, M. Said. Gradient-Based Optimizer for Parameter Extraction in Photovoltaic Models. IEEE Access, (2021) 9, 13403-13416.
  15. D.Yousri, M. Abd Elaziz, L. Abualigah, D. Oliva, M. A. Al-qaness, A. A. Ewees, A. A. COVID-19 X-ray images classification based on enhanced fractional-order cuckoo search optimizer using heavy-tailed distributions. Applied Soft Computing, (2021) 107052.
  16. M. Micev, M. Ćalasan, D. Oliva. Design and robustness analysis of an Automatic Voltage Regulator system controller by using Equilibrium Optimizer algorithm. Computers & Electrical Engineering, (2021) Vol. 89, 106930.
  17. G. Dhiman, D. Oliva, A. Kaur, K. K. Singh, S. Vimal, A. Sharma, K. Cengiz. BEPO: A novel binary emperor penguin optimizer for automatic feature selection. Knowledge-Based Systems, (2021) Vol. 211, 106560.
  18. I. Aranguren, A. Valdivia, B. Morales-Castañeda, D. Oliva, M. Abd Elaziz, M. Perez-Cisneros. Improving the segmentation of magnetic resonance brain images using the LSHADE optimization algorithm. Biomedical Signal Processing and Control, (2020) Vol. 64, 102259.
  19. A. Hernandez, I. Aranguren, D. Oliva, M. Abd Elaziz, E Cuevas. Efficient image segmentation through 2D histograms and an improved owl search algorithm. International Journal of Machine Learning and Cybernetics, 2020 1-20.
  20. A. A. Ewees, M. Abd Elaziz, D. Oliva. A new multi-objective optimization algorithm combined with opposition-based learning. Expert Systems with Applications, (2021) Vol .165, 113844.
  21. D. Oliva, P. Copado, S. Hinojosa, J. Panadero, D. Riera, A. A. Juan. Fuzzy Simheuristics: Solving Optimization Problems under Stochastic and Uncertainty Scenarios. Mathematics, 2020, 8(12), 2240.
  22. A. G. Hussien, D. Oliva, E. H. Houssein, A. A. Juan, X. Yu. Binary Whale Optimization Algorithm for Dimensionality Reduction. Mathematics, 2020, 8(10), 1821.
  23. D. Yousri, M. Abd Elaziz, D. Oliva, L. Abualigah, M. A. Al-qaness, A. A. Ewees. Reliable applied objective for identifying simple and detailed photovoltaic models using modern metaheuristics: Comparative study. Energy Conversion and Management, 2020, Vol. 223, 113279.
  24. E. H. Houssein, M. E. Hosney, M. Elhoseny, D. Oliva, W. M Mohamed, M. Hassaballah. Hybrid Harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics. Scientific Reports,2020, Vol. 10(1), 1-22.
  25. N. Ortega-Sánchez, D. Oliva, E. Cuevas, M. Pérez-Cisneros, A. A. Juan. An Evolutionary Approach to Improve the Halftoning Process. Mathematics, 2020, Vol. 8(9), 1636.
  26. I. López-López, G. Sosa-Gómez, C. Segura, D. Oliva, O. Rojas. Metaheuristics in the Optimization of Cryptographic Boolean Functions. Entropy, 2020, Vol. 22(9), 1052.
  27. A. Bala, I. Ismail, R. Ibrahim, S. M. Sait, D. Oliva. An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines. IEEE Access, 2020 Vol. 8, 159773-159789.
  28. M. Micev, M. Ćalasan, D. Oliva. Fractional order PID controller design for an AVR system using Chaotic Yellow Saddle Goatfish Algorithm. Mathematics, 2020, Vol. 8(7), 1182.
  29. G. R. Hernández, M. A. Navarro, N. Ortega-Sánchez, D. Oliva, M Pérez-Cisneros. Failure Detection on Electronic Systems Using Thermal Images and Metaheuristic Algorithms. IEEE Latin America Transactions, 2020, Vol 18(08), 1371-1380.
  30. E. Rodríguez-Esparza, L. A. Zanella-Calzada, D. Oliva, A. A. Heidari, D. Zaldivar, M. Pérez-Cisneros, L. K. Foong. “An Efficient Harris Hawks-inspired Image Segmentation Method”. Expert Systems with Applications, Vol. 155 (2020) 113428.
  31. Boudjemaa, D. Oliva, F. Ouaar. Fractional Lévy flight bat algorithm for global optimisation. International Journal of Bio-Inspired Computation, 2020 Vol.15 No.2, pp.100 – 112. DOI: https://dx.doi.org/10.1504/IJBIC.2020.106441
  32. M. Rizk-Allah, A. E. Hassanien, D. Oliva. An enhanced sitting–sizing scheme for shunt capacitors in radial distribution systems using improved atom search optimization. Neural Computing & Applications (2020), First online 13 March 2020. DOI: https://doi.org/10.1007/s00521-020-04799-6
  33. M. Abd Elaziz, U. Sarkar, S. Nag, S. Hinojosa,  D. Oliva. Improving image thresholding by the type II fuzzy entropy and a hybrid optimization algorithm. Soft Computing (2020), First online 13 March 2020. DOI: https://doi.org/10.1007/s00500-020-04842-7
  34. Abbassi, R. Abbassi, A. A. Heidari, D. Oliva, H. Chen, A. Habib, M. Jemli, M. Wang. Parameters identification of photovoltaic cell models using enhanced exploratory salp chains-based approach, Energy, Vol. 198 (2020),117333. DOI: https://doi.org/10.1016/j.energy.2020.117333
  35. S. Naji Alwerfali, M. A. A. Al-qaness, M. Abd Elaziz, A. A. Ewees, D. Oliva, S. Lu. Multi-Level Image Thresholding Based on Modified Spherical Search Optimizer and Fuzzy Entropy. Entropy 2020, 22, 328. DOI: https://doi.org/10.3390/e22030328
  36. D. Oliva, M. A. Elaziz, M.A. An improved brainstorm optimization using chaotic opposite-based learning with disruption operator for global optimization and feature selection. Soft Computing (2020), First online 26 February 2020. DOI: https://doi.org/10.1007/s00500-020-04781-3
  37. D. Oliva, M. S.R. Martins, V. Osuna-Enciso, R. F. de Morais, Combining information from thresholding techniques through an evolutionary Bayesian network algorithm. Applied Soft Computing , Volume 90(2020), 106147. DOI: https://doi.org/10.1016/j.asoc.2020.106147
  38. M. Ahmad, S. Shabbir, D. Oliva, M. Mazzara, S. Distefano. Spatial-prior generalized fuzziness extreme learning machine autoencoder-based active learning for hyperspectral image classification. Optik, Vol. 206 (2020), 163712. DOI: https://doi.org/10.1016/j.ijleo.2019.163712
  39. A. Elaziz, A. A. Ewees, D. Oliva. Hyper-heuristic method for multilevel thresholding image segmentation. Expert Systems with Applications, Volume 146 (2020), 113201. DOI: https://doi.org/10.1016/j.eswa.2020.113201
  40. E. H. Houssein, M. E. Hosney, D. Oliva, W. M. Mohamed, M. Hassaballah. A Novel Hybrid Harris Hawks Optimization and Support Vector Machines for Drug Design and Discovery. Computers & Chemical Engineering, Vol13 (2020) 106656. DOI: https://doi.org/10.1016/j.compchemeng.2019.106656
  41. O. Maciel, A. Valdivia, D. Oliva, E. Cuevas, D. Zaldivar, M. Perez-Cisneros, “A novel hybrid metaheuristic optimization method: hypercube natural aggregation algorithm”. Soft Computing (2019), First online October 23, 2019. DOI: https://doi.org/10.1007/s00500-019-04416-2
  42. D. Oliva, S. Nag, M. A. Elaziz, U. Sarkar, S. Hinojosa, “Multilevel thresholding by fuzzy type II sets using evolutionary algorithms”. Swarm and Evolutionary Computation, Volume 51 (2019), 100591. DOI https://doi.org/10.1016/j.swevo.2019.100591
  43. Hinojosa, D. Oliva, E. Cuevas, G. Pajares, D. Zaldivar, M. Pérez-Cisneros, “Reducing overlapped pixels: a multi-objective color thresholding approach”. Soft Computing (2019), First online September 3, 2019. DOI: https://doi.org/10.1007/s00500-019-04315-6
  44. D. Oliva, M. A. Elaziz, A. H. Elsheikh, A. A. Ewees, “A review on meta-heuristics methods for estimating parameters of solar cells”. Journal of Power Sources, (2019) 126683. DOI: https://doi.org/10.1016/j.jpowsour.2019.05.089
  45. R. A. Ibrahim, M. A. Elaziz, D. Oliva, S. Lu, “An improved runner-root algorithm for solving feature selection problems based on rough sets and neighborhood rough sets”. Applied Soft Computing. First online 23 May 2019, 105517. DOI: https://doi.org/10.1016/j.asoc.2019.105517
  46.  H. Jia, C. Lang, D. Oliva, W. Song, X. Peng, “Dynamic Harris Hawks Optimization with Mutation Mechanism for Satellite Image Segmentation”. Remote Sensing. 2019, 11, 1421. DOI: https://doi.org/10.3390/rs11121421
  47. R. A. Ibrahim, M. A.  Elaziz, D. Oliva, E. Cuevas, S. Lu, «An opposition-based social spider optimization for feature selection», Soft Computing, First online  18 March 2019, DOI: https://doi.org/10.1007/s00500-019-03891-x
  48. H. Jia, C. Lang, D. Oliva, W. Song, X. Peng, “Hybrid Grasshopper Optimization Algorithm and Differential Evolution for Multilevel Satellite Image Segmentation”. Remote Sensing. 2019, 11, 1134. DOI: https://doi.org/10.3390/rs11091134
  49. H. Jia, X. Peng, W. Song, D. Oliva, C. Lang, Y. Li, “Masi Entropy for Satellite Color Image Segmentation Using Tournament-Based Lévy Multiverse Optimization Algorithm”. Remote Sensing. 2019, 11, 942. DOI: https://doi.org/10.3390/rs11080942
  50. M. A. Elaziz, D. Oliva, A. A. Ewees, «Multi-level thresholding-based grey scale image segmentation using multi-objective multi-verse optimizer», Expert Systems with Applications, Volume 125 (2019), 112-129, DOI: https://doi.org/10.1016/j.eswa.2019.01.047
  51. D. Zaldivar, E. Cuevas, O. Maciel, A. Valdivia, E. Chavolla, D. Oliva, «Learning classical and metaheuristic optimization techniques by using an educational platform based on LEGO robots», The International Journal of Electrical Engineering & Education, Available online January 21 2019. DOI: https://doi.org/10.1177/0020720918822738
  52. A. M. Anter, A. E. Hassenian, D. Oliva,»An improved fast fuzzy c-means using crow search optimization algorithm for crop identification in agricultural», Expert Systems with Applications, Volume 118 (2019), 340-354, DOI: https://doi.org/10.1016/j.eswa.2018.10.009
  53. A. A. Ewees, M. A. Elaziz, D. Oliva, «Image segmentation via multilevel thresholding using hybrid optimization algorithms», Journal of Electronic Imaging, Volume 27(6), 063008, November 2018, DOI: https://doi.org/10.1117/1.JEI.27.6.063008
  54. S. Hinojosa, K. G. Dhal, M. A. Elaziz, D.Oliva, E. Cuevas, «Entropy-based imagery segmentation for breast histology using the stochastic fractal search», Neurocomputing, Volume 321(2018),201-215, DOI: https://doi.org/10.1016/j.neucom.2018.09.034
  55. R. A. Ibrahim, A. A. Ewees, D. Oliva, M. A. Elaziz, S. Lu, «Improved salp swarm algorithm based on particle swarm optimization for feature selection», J Ambient Intelligence and Humanized Computing, Available online 11 September 2018, DOI: https://doi.org/10.1007/s12652-018-1031-9
  56. M.A. Diaz-Cortes, N. Ortega-Sanchez, S. Hinojosa, D. Oliva, E. Cuevas, R. Rojas, A. Demin, «A multi-level, thresholding method for breast thermograms analysis using dragonfly algorithm «, Infrared Physics & Technology, Available online 16 August 2018, DOI: https://doi.org/10.1016/j.infrared.2018.08.007
  57. S. Hinojosa, O. Avalos, D. Oliva, E. Cuevas, G. Pajares, D. Zaldivar, J. Galvez, «Unassisted Thresholding based on Multi-Objective Evolutionary Algorithms», Knowledge-Based Systems, Available online 6 July 2018, DOI: https://doi.org/10.1016/j.knosys.2018.06.028
  58. M. A. Elaziz, D. Oliva, «Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm», Energy Conversion and Management, Vol. 171, 1 September 2018, Pages 1849-1859, DOI:  https://doi.org/10.1016/j.enconman.2018.05.062
  59. M. Elhoseny, D. Oliva, V. Osuna-Enciso,  A. E. Hassanien, M. Gunasekaran, «Parameter identification of two dimensional digital filters using electro-magnetism optimization», Multimedia Tools and Applications, Available online 11 May 2018, DOI: https://doi.org/10.1007/s11042-018-6095-1
  60. D. Oliva, S. Hinojosa, M.A. El Aziz, N. Ortega-Sanchez, «Context based image segmentation using antlion optimization and sine cosine algorithm», Multimedia Tools and Applications, Available online 14 March 2018, DOI: https://doi.org/10.1007/s11042-018-5815-x
  61. R, Boudjemaa, D. Oliva, «A multi-objective approach to weather radar network architecture», Soft Computing, Available online 14 February 2018, DOI: https://doi.org/10.1007/s00500-018-3072-6
  62. M. Issa,  A. E. Hassanien, D. Oliva, A. Helmi, I. Ziedan, A. Alzohairy, «ASCA-PSO: Adaptive sine cosine optimization algorithm integrated with particle swarm for pairwise local sequence alignment», Expert Systems with Applications, Volume 99 (2018), 56-70, DOI:  https://doi.org/10.1016/j.eswa.2018.01.019
  63. J. Gálves, E. Cuevas, O. Avalos, D. Oliva, S. Hinojosa, «Electromagnetism-like mechanism with collective animal behavior for multimodal optimization», Applied Intelligence, Available online 13 December 2017, DOI: https://doi.org/10.1007/s10489-017-1090-1
  64. S. Hinojosa, D. Oliva, E. Cuevas, G. Pajares, O. Avalos, J. Gálves,»Improving multi-criterion optimization with chaos: a novel Multi-Objective Chaotic Crow Search Algorithm», Neural Computing and Applications, Available online 26 October 2017, DOI: https://doi.org/10.1007/s00521-017-3251-x
  65. M.A. El Aziz, A. M. Hemdan, A. E. Hassanien, D. Oliva, S. Xiong, «Analysis of bioactive amino acids from fish Hydrolysates with a new bioinformatic intelligent system approach», Scientific Reports, Nature  (7), Article number: 10860 (2017), DOI: https://doi.org/10.1038/s41598-017-10890-1
  66. D. Oliva, S. Hinojosa, V. Osuna-Enciso, E. Cuevas, M. Pérez-Cisneros, G. Sanchez-Ante, «Image segmentation by minimum cross entropy using evolutionary methods», Soft Computing, Available online 30 August 2017, DOI: https://doi.org/10.1007/s00500-017-2794-1
  67. M.A. El Aziz, D. Oliva, S. Xiong, «An Improved Opposition-Based Sine Cosine Algorithm for Global Optimization», Expert Systems with Applications, Available online 15 August 2017, DOI: https://doi.org/10.1016/j.eswa.2017.07.043
  68. D. Oliva, A. A. Ewees, M. A. El Aziz, A. E. Hassanien, M. Pérez-Cisneros, «A Chaotic Improved Artificial Bee Colony for Parameter Estimation of Photovoltaic Cells», Energies, Volume 10 (7), 865, June 2017. DOI: http://dx.doi.org/10.3390/en10070865
  69. D. Oliva, M. A. El Aziz, A. E. Hassanien. «Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm», Applied Energy, Volume 200, 15 August 2017, pp 141-154. DOI: https://doi.org/10.1016/j.apenergy.2017.05.029
  70. D. Oliva, S. Hinojosa, E. Cuevas, G. Pajares, O. Avalos, J. Gálvez. «Cross entropy based thresholding for magnetic resonance brain images using Crow Search Algorithm», Expert Systems with Applications, Vol 79, 15 August 2017, Pages 164-180. DOI: http://dx.doi.org/10.1016/j.eswa.2017.02.042
  71. V. Osuna-Enciso, E. Cuevas, D. Oliva, V. Zúñiga, M. Pérez-Cisneros, and D. Zaldívar, “A multi-objective approach to homography estimation”, Computational Intelligence and Neuroscience, Volume 2016 (2016), Article ID 3629174,. DOI: http://dx.doi.org/10.1155/2016/3629174
  72. V. Osuna-enciso, E. Cuevas, H. Sossa, D. Oliva, and M. Perez-Cisneros. A bio-inspired evolutionary algorithm: allostatic optimisation. Int. J. Bio-Inspired Computation, vol. 8 (3), pp. 158-169, 2016. DOI: http://dx.doi.org/10.1504/IJBIC.2016.076633
  73. D. Oliva, V. Osuna-Enciso, E. Cuevas, G. Pajares, M. Pérez-Cisneros, and D. Zaldívar. “Improving segmentation velocity using an evolutionary method”, Expert Systems with Applications, vol 42, no. 14, pp. 5874–5886, 2015. DOI: http://dx.doi.org/10.1016/j.eswa.2015.03.028
  74. E. Cuevas, V. Osuna-Enciso, and D. Oliva, “Circle detection on images based on the Clonal Selection Algorithm (CSA)”, Imaging Sci. J., vol. 63, no. 1, pp. 34–44, 2015. DOI: http://dx.doi.org/10.1179/1743131X14Y.0000000079
  75. D. Oliva, E. Cuevas, G. Pajares, D. Zaldivar, and V. Osuna, “A Multilevel thresholding algorithm using electromagnetism optimization”, Neurocomputing, vol. 139, pp. 357–381, 2014. DOI: http://dx.doi.org/10.1016/j.neucom.2014.02.020
  76. D. Oliva, E. Cuevas, and G. Pajares, “Parameter identification of solar cells using artificial bee colony optimization”, Energy, vol. 72, pp. 93–102, 2014. DOI: http://dx.doi.org/10.1016/j.energy.2014.05.011
  77. D. Oliva, E. Cuevas, G. Pajares, and D. Zaldivar, “Template matching using an improved electromagnetism-like algorithm,” Appl. Intell., 2014. DOI: http://dx.doi.org/10.1007/s10489-014-0552-y
  78. E. Cuevas, D. Zaldívar, M. Pérez-Cisneros, and D. Oliva, “Block-matching algorithm based on differential evolution for motion estimation,” Eng. Appl. Artif. Intell., vol. 26, pp. 488–498, 2013. DOI: http://dx.doi.org/10.1016/j.engappai.2012.08.003
  79. D. Oliva, E. Cuevas, G. Pajares, D. Zaldivar, and M. Perez-Cisneros, “Multilevel thresholding segmentation based on harmony search optimization,” J. Appl. Math., vol. 2013, 2013. DOI: http://dx.doi.org/10.1155/2013/575414
  80. E. Cuevas, D. Oliva, M. Díaz, D. Zaldivar, M. Pérez-Cisneros, and G. Pajares, “White blood cell segmentation by circle detection using electromagnetism-like optimization,” Comput. Math. Methods Med., vol. 2013, 2013. DOI: http://dx.doi.org/10.1155/2013/395071
  81. E. Cuevas, D. Oliva, D. Zaldivar, M. Pérez-Cisneros, and H. Sossa, “Circle detection using electro-magnetism optimization,” Inf. Sci. (Ny)., vol. 182, no. 1, pp. 40–55, 2012. DOI: http://dx.doi.org/10.1016/j.ins.2010.12.024
  82. E. Cuevas, D. Oliva, Z. D., M. Pérez-Cisneros, and G. Pajares, “Opposition-based electromagnetism-like for global optimization,” Int. J. Innov. Comput. Inf. Control, vol. 8, no. 12, pp. 8181–8198, 2012. http://www.ijicic.org/ijicic-11-09076.pdf

Publications in Mexican journals

  1.  O. Avalos, E. V. Cuevas Jimenez, A. Valdivia-González, J. Gálvez, S. Hinojosa, D. Zaldívar, D. Oliva, «A Comparative Study of Evolutionary Computation Techniques for Solar Cells Parameter Estimation» Computacion y Sistemas, Vol 23 (1) 2019, 231-256, http://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/2881
  2.  J. V. Osuna Enciso, J. I. Espinoza Haro, D. Oliva, I. F. Hernández Ahuactzi, «Offshore Wind Farm Layout Optimization via Differential Evolution», Computacion y Sistemas, Vol. 22(3), 2018, 929-941. http://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/2688
  3. E. Estrada, R. Maciel, C. A. Ochoa, B. Bernabe-Loranca, D. Oliva, V. Larios, «Smart city visualization tool for the open data georeferenced analysis utilizing machine learning», International Journal of Combinatorial Optimization Problems and Informatics, 9(2), 25-40. https://ijcopi.org/index.php/ojs/article/view/93
  4. Y. Oliva-Romerom A. Ochoa-Zezzatti, A. Marcela-Herrera,  D. A. Oliva-Navarro, «Modelo innovador para un aparador comercial usando un algoritmo competitivo imperialista», Research in Computing Science, Volume 134 (2017),  35-44   http://www.rcs.cic.ipn.mx/rcs/2017_134/
  5. E. Cuevas-Jiménez and D. A. Oliva-Navarro, “Modelado de filtros IIR usando un algoritmo inspirado en el electromagnetismo, IIR Filter Modeling Using an Algorithm Inspired on Electromagnetism,” Rev. Ing. Investig. y Tecnol., vol. XIV, no. 01, pp. 125–138, 2013.  DOI: http://dx.doi.org/10.1016/S1405-7743(13)72231-5
  6. E. Cuevas, D. Oliva, V. Osuna-Enciso, F. Wario, “Detección de primitivas circulares usando un algoritmo inspirado en el electromagnetismo, Circle Detection Using an Electromagnetism-Inspired Algorithm,” Rev. Ing. Investig. y Tecnol., vol. XII, no. 4, pp. 469–485, 2011. http://www.revistas.unam.mx/index.php/ingenieria/article/view/27897/25818
  7. E. Cuevas, V. Osuna-Enciso, D. Oliva, and F. Wario, “Segmentación y detección de glóbulos blancos en imágenes usando Sistemas Inmunes Artificiales,” Rev. Mex. Ing. Biomédica, vol. 31, no. 2, pp. 119–134, 2010. http://www.medigraphic.com/pdfs/inge/ib-2010/ib102f.pdf

Publications in peer-reviewed conferences and congresses

  1. A. El-dosuky, D. Oliva, A. E. Hassanien. An Artificial Intelligence System for Apple Fruit Disease Classification Based on Support Vector Machine and Cockroach Swarm Optimization. In Joint European-US Workshop on Applications of Invariance in Computer Vision (pp. 137-147). Springer, Cham.
  2. A. A. Abd El-aziz, A. Darwish, D. Oliva, A. E. Hassanien. Machine Learning for Apple Fruit Diseases Classification System. In Joint European-US Workshop on Applications of Invariance in Computer Vision (pp. 16-25). Springer, Cham.
  3. Garcia, A. Ochoa-Zezzatti, A. Martínez-Retamoza, G. Ochoa, L. Aguilar, D. Oliva, J. Mejía. Use of Deep Learning for Bird Detection to Reduction of Collateral Damage in Fruit Fields. In Joint European-US Workshop on Applications of Invariance in Computer Vision (pp. 381-392). Springer, Cham.
  4. E. Rodríguez-Esparza, L. A. Zanella-Calzada, D. Oliva, M Pérez-Cisneros. Automatic detection and classification of abnormal tissues on digital mammograms based on a bag-of-visual-words approach. In Medical Imaging 2020: Computer-Aided Diagnosis (Vol. 11314, p. 1131424). International Society for Optics and Photonics.
  5. Abd Elaziz, S. Lu, D. Oliva, M El-Abd. Improved Moth-Flame Optimization Based on Opposition-Based Learning for Feature Selection. In 2019 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 3017-3024). IEEE.
  6. Oliva, S. Hinojosa, M. S. Martins, E. Rodriguez-Esparza, N. Ortega-Sánchez, M. Pérez-Cisneros. Improving the estimation of parameters in induction motors using an evolutionary computation algorithm. In 2019 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1-6). IEEE.
  7. Rodríguez-Esparza, L. A. Zanella-Calzada, D. Oliva. S. Hinojosa, M. Pérez-Cisneros. Multilevel segmentation for automatic detection of malignant masses in digital mammograms based on threshold comparison. In 2019 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1-6). IEEE.
  8. El Yafrani, M. Scoczynski, M. Delgado, R. Lüders, I. Sung, M. Wagner, D. Oliva. On updating probabilistic graphical models in Bayesian Optimisation Algorithm. In 2019 8th Brazilian Conference on Intelligent Systems (BRACIS) (pp. 311-316). IEEE.
  9. D. Oliva and M. S. R. Martins, «A Bayesian based Hyper-Heuristic approach for global optimization,» 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand, 2019, pp. 1766-1773.
  10.  T. O. Camargo, D. Pechebovicz, S. M. Premebida, V. R. Soares, V. Baroncini, H. Siqueira, D. Oliva, and M. Martins, “Detecting a predefined solar spot group with a pretrained convolutional neural network,” 2019 IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI), Barranquilla, Colombia, 2019, pp. 1-6.
  11. R. Contreras, A. Ochoa, E. Cossío, V. García, D. Oliva, R. Torres. “Design and Implementation of an IoT-Based Háptical Interface Implemented by Memetic Algorithms to Improve Competitiveness in an Industry 4.0 Model for the Manufacturing Sector”. In: Abraham A., Gandhi N., Pant M. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2018. Advances in Intelligent Systems and Computing, vol 939. Springer, Cham
  12. S. Hinojosa, O. Avalos, J. Gálvez, D. Oliva, E. Cuevas and M. Pérez-Cisneros, «Remote sensing imagery segmentation based on multi-objective optimization algorithms,» 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI), Guadalajara, Mexico, 2018, pp. 1-6.
  13. A. Ochoa and D. Oliva, «Smart traffic management to support people with color blindness in a Smart City,» 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI), Guadalajara, Mexico, 2018, pp. 1-8.
  14. S. Hinojosa, D. Oliva, E. Cuevas, M. Pérez-Cisneros and G. Pájares, «Real-time video thresholding using evolutionary techniques and cross entropy,» 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), Rhodes, 2018, pp. 1-8.
  15. D. Oliva, A. Demin, M. Demeshko, “Edge detection using neural network committee.” 28th International Conference on Computer Graphics and Vision, September 24-27, 2018, Tomsk, Russia, pp. 66-69.
  16. M. A. Elaziz, A. A. Ewees, D. Oliva, P. Duan, S. Xiong. “A Hybrid Method of Sine Cosine Algorithm and Differential Evolution for Feature Selection”. In: Liu D., Xie S., Li Y., Zhao D., El-Alfy ES. (eds) Neural Information Processing. ICONIP 2017, Guangzhou, China. Lecture Notes in Computer Science, vol 10638. Springer, Cham
  17. R. A. Ibrahim, D. Oliva, A.A. Ewees, S. Lu. “Feature Selection Based on Improved Runner-Root Algorithm Using Chaotic Singer Map and Opposition-Based Learning”. In: Liu D., Xie S., Li Y., Zhao D., El-Alfy ES. (eds) Neural Information Processing. ICONIP 2017, Guangzhou, China. Lecture Notes in Computer Science, vol 10638. Springer, Cham

Books

Authored books

  1. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa, «Metaheuristic Algorithms for Image Segmentation: Theory and Applications», Studies in Computational Intelligence, Vol 825, Spinger International Publishing. March 2019, DOI: https://doi.org/10.1007/978-3-030-12931-6
  2. Erik Cuevas, Valentin Osuna-Enciso, Diego Oliva,  «Evolutionary Computation Techniques: A Comparative Perspective», Studies in Computational Intelligence, Vol. 686, Springer International Publishing. January 2017. DOI: http://dx.doi.org/10.1007/978-3-319-51109-2.
  3. Diego Oliva, Erik Cuevas, «Advances and Applications of Optimised Algorithms in Image Processing», Intelligent Systems Reference Library, Vol. 117, Springer International Publishing.  January 2017. DOI: http://dx.doi.org/10.1007/978-3-319-48550-8.
  4. Erik V. Cuevas Jiménez, Diego A. Oliva Navarro, José V. Osuna Enciso, Margarita A. Diaz Cortes. “Optimización: Algoritmos programados con Matlab”. Primera Edición, Alfaomega Grupo Editor, México, June 2016.
  5. Erik Valdemar Cuevas Jimenez, Margarita Díaz Cortes, Diego Oliva Navarro, «Advances of Evolutionary Computation: Methods and Operators», Studies in Computational Intelligence, Vol. 629,  Springer International Publishing.  January 2016. DOI: http://dx.doi.org/10.1007/978-3-319-28503-0.

Edited books

  1. Diego Oliva, Salvador Hinojosa (Eds), “Applications of Hybrid Metaheuristic Algorithms for Image Processing”, Studies in Computational Intelligence, Vol.890, Springer International Publishing. March 2020. DOI: https://doi.org/10.1007/978-3-030-40977-7 
  2. Aboul Ella Hassanien, Diego Alberto Oliva (Eds), «Advances in Soft Computing and Machine Learning in Image Processing», Studies in Computational Intelligence, Vol. 730,  Springer International Publishing. January 2018. DOI: http://dx.doi.org/10.1007/978-3-319-63754-9

Book chapters

  1. Oliva, Diego and Aboul Ella Hassanien. «Digital Images Segmentation Using a Physical-Inspired Algorithm.» Handbook of Research on Machine Learning Innovations and Trends. Aboul Ella Hassanien and Tarek Gaber, IGI Global, 2017. pp 975-996. Web. 2 May. 2017. DOI: http://dx.doi.org/10.4018/978-1-5225-2229-4.ch043
  2. V. Osuna-Enciso , V. Zúñiga, D. Oliva, E. Cuevas and Humberto Sossa,” Image Segmentation Using an Evolutionary Method Based on Allostatic Mechanisms”, in Image Feature Detectors and Descriptors, Studies in Computational Intelligence, Vol 630, Ali Ismail Awad and Mahmoud Hassaballah, Springer International Publishing, 2016. DOI: http://dx.doi.org/10.1007/978-3-319-28854-3_10

  3. D. Oliva, E. Cuevas, G. Pajares, D. Zaldívar, M. Pérez-Cisneros, and V. Osuna-Enciso, “Harmony Search Optimization for Multilevel Thresholding in Digital Images”, in Evolutionary Computation Techniques and Applications, Ashish M. Gujarathi, B. V. Babu. Apple Academic Press, CRC Press,Taylor and Francis.

  4. E. Cuevas, D. Oliva, D. Zaldivar, M. Pérez, and R. Rojas, “Circle Detection Algorithm Based on Electromagnetism-Like Optimization,” in Handbook of Optimization, Intelligen., I. Zelinka, V. Snášel, and A. Abraham, Eds. Springer Berlin Heidelberg, 2013, pp. 907–934. DOI: http://dx.doi.org/10.1007/978-3-642-30504-7_36