publications

2025

1. Improving prototypical parts abstraction for case-based reasoning explanations designed for the kidney stone type recognition

   Daniel Flores-Araiza, Francisco Lopez-Tiro, Clément Larose, Salvador Hinojosa, Andres Mendez-Vazquez, and 3 more authors

   Artificial Intelligence in Medicine, 2025
2. Beyond SWE-Bench: A Compiler-Assisted Pipeline for Multi-language Automated Program Repair

   Moises Pineda, Diego Luna, Mariana Esquivel, Jesús Bours, Juan Salazar, and 2 more authors

   In Mexican International Conference on Artificial Intelligence, 2025
3. SLICE: Semantic Language-Indexed Code Extraction with Backward Slicing for Repository-Scale Code Generation

   Oscar Eduardo Arámbula Vega, Oscar Beltran, Omar Guzmán, Victor Terron-Macias, and Salvador Hinojosa

   In NeurIPS 2025 Workshop on LatinX in AI, 2025

   Poster presentation
4. OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD

   Enrique Garcia-Ceja, Andrea Stautland, Michael A Riegler, Pål Halvorsen, Salvador Hinojosa, and 6 more authors

   Scientific Data, 2025
5. Evolutionary Algorithms in Code Smell Detection: A Feature Selection Approach for Software Engineering

   Diego Avalos and Salvador Hinojosa

   In Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions, 2025

   Abs DOI

   This chapter delves into how evolutionary algorithms (EAs) can be applied to identify code smells, framing it as a problem of selecting features in software code metrics. Code smells, which signal potential flaws in software design, typically demand labor intensive techniques for their detection. We investigate the efficiency of EA driven strategies that optimize the selection of features related to code quality, ultimately improving the precision and effectiveness of detecting code smells. We cover the basics of code smells and evolutionary algorithms, then detail our methodology for using EAs to select features that significantly improve code smell classification. Through experiments on industry-relevant software datasets, our approach is shown to improve traditional rule-based methods in detection accuracy. The chapter concludes with implications for future research and the potential of AI-enhanced solutions in software engineering.

2024

1. Improving Prostate Image Segmentation Based on Equilibrium Optimizer and Cross-Entropy.

   Omar Zarate, Salvador Hinojosa, and Daniel Ortiz-Joachin

   Applied Sciences (2076-3417), 2024

2022

1. An optimized Kernel Extreme Learning Machine for the classification of the autism spectrum disorder by using gaze tracking images

   Angel Gaspar, Diego Oliva, Salvador Hinojosa, Itzel Aranguren, and Daniel Zaldivar

   Applied Soft Computing, 2022
2. Population-based self-adaptive Generalised Masi Entropy for image segmentation: A novel representation

   Seyed Jalaleddin Mousavirad, Diego Oliva, Ripon K Chakrabortty, Davood Zabihzadeh, and Salvador Hinojosa

   Knowledge-Based Systems, 2022
3. Improving the Convergence and Diversity in Differential Evolution Through a Stock Market Criterion

   Mario A Navarro, Alfonso Ramos-Michel, Angel Gaspar, Diego Oliva, Salvador Hinojosa, and 2 more authors

   In International Conference on the Applications of Evolutionary Computation (Part of EvoStar), 2022
4. A hyper-heuristic guided by a probabilistic graphical model for single-objective real-parameter optimization

   Diego Oliva, Marcella SR Martins, Salvador Hinojosa, Mohamed Abd Elaziz, Paulo Victor Santos, and 2 more authors

   International Journal of Machine Learning and Cybernetics, 2022
5. Handling stagnation through diversity analysis: A new set of operators for evolutionary algorithms

   Bernardo Morales-Castaneda, Oscar Maciel-Castillo, Mario A Navarro, Itzel Aranguren, Arturo Valdivia, and 3 more authors

   In 2022 IEEE Congress on Evolutionary Computation (CEC), 2022
6. Modern Metaheuristics in Image Processing

   Diego Oliva, Noe Ortega-Sánchez, Salvador Hinojosa, and Marco Pérez-Cisneros

   2022

2021

1. Kernel Recursive Least Square Approach for Power System Harmonic Estimation

   Omar Avalos, Erik Cuevas, Héctor G Becerra, Jorge Gálvez, Salvador Hinojosa, and 1 more author

   Electric Power Components and Systems, 2021

   DOI
2. HCS-BBD: an effective population-based approach for multi-level thresholding

   Seyed Jalaleddin Mousavirad, Gerald Schaefer, Diego Oliva, and Salvador Hinojosa

   2021

   DOI
3. Opposition-based moth swarm algorithm

   Diego Oliva, Sara Esquivel-Torres, Salvador Hinojosa, Marco Pérez-Cisneros, Valentı́n Osuna-Enciso, and 3 more authors

   Expert Systems with Applications, 2021
4. Metaheuristics in Machine Learning: Theory and Applications

   Diego Oliva, Essam H Houssein, and Salvador Hinojosa

   2021

   DOI
5. Differential Evolution-based Neural Network Training Incorporating a Centroid-based Strategy and Dynamic Opposition-based Learning

   Seyed Jalaleddin Mousavirad, Diego Oliva, Salvador Hinojosa, and Gerald Schaefer

   2021

   DOI

2020

1. Applications of Hybrid Metaheuristic Algorithms for Image Processing

   Diego Oliva and Salvador Hinojosa

   2020

   DOI
2. Side-Blotched Lizard Algorithm: A polymorphic population approach

   O. Maciel C., E. Cuevas, M.A. Navarro, D. Zaldívar, and Salvador Hinojosa

   Applied Soft Computing Journal, 2020

   cited By 0

   DOI
3. Balancing the Influence of Evolutionary Operators for Global optimization

   D. Oliva, E. Rodriguez-Esparza, M. S. R. Martins, M. Abd Elaziz, Salvador Hinojosa, and 2 more authors

   2020

   DOI
4. Fuzzy Simheuristics: Solving Optimization Problems under Stochastic and Uncertainty Scenarios

   Diego Oliva, Pedro Copado, Salvador Hinojosa, Javier Panadero, Daniel Riera, and 1 more author

   Mathematics, 2020

   DOI

2019

1. Reducing overlapped pixels: a multi-objective color thresholding approach

   Salvador Hinojosa, D. Oliva, E. Cuevas, G. Pajares, D. Zaldivar, and 1 more author

   Soft Computing, 2019

   DOI
2. A reactive model based on neighborhood consensus for continuous optimization

   J. Gálvez, E. Cuevas, Salvador Hinojosa, O. Avalos, and M. Pérez-Cisneros

   Expert Systems with Applications, 2019

   DOI
3. Remote sensing imagery segmentation based on multi-objective optimization algorithms

   Salvador Hinojosa, O. Avalos, J. Galvez, D. Oliva, E. Cuevas, and 1 more author

   2019

   cited By 0

   DOI
4. Metaheuristic Algorithms for Image Segmentation: Theory and Applications

   Diego Oliva, Mohamed Abd Elaziz, and Salvador Hinojosa

   2019

   DOI
5. A comparative study of evolutionary computation techniques for solar cells parameter estimation

   O. Avalos, E. Cuevas, A. Valdivia-González, J. Gálvez, Salvador Hinojosa, and 2 more authors

   Computacion y Sistemas, 2019

   cited By 0

   DOI
6. Multilevel thresholding by fuzzy type II sets using evolutionary algorithms

   D. Oliva, S. Nag, M.A. Elaziz, U. Sarkar, and Salvador Hinojosa

   Swarm and Evolutionary Computation, 2019

   cited By 0

   DOI

2018

1. Entropy-based imagery segmentation for breast histology using the Stochastic Fractal Search

   Salvador Hinojosa, K.G. Dhal, M.A. Elaziz, D. Oliva, and E. Cuevas

   Neurocomputing, 2018

   DOI
2. Unassisted thresholding based on multi-objective evolutionary algorithms

   Salvador Hinojosa, O. Avalos, D. Oliva, E. Cuevas, G. Pajares, and 2 more authors

   Knowledge-Based Systems, 2018

   DOI
3. Context based image segmentation using antlion optimization and sine cosine algorithm

   D. Oliva, Salvador Hinojosa, M.A. Elaziz, and N. Ortega-Sánchez

   Multimedia Tools and Applications, 2018

   DOI
4. Electromagnetism-like mechanism with collective animal behavior for multimodal optimization

   J. Gálvez, E. Cuevas, O. Avalos, D. Oliva, and Salvador Hinojosa

   Applied Intelligence, 2018

   DOI
5. Real-Time video thresholding using evolutionary techniques and cross entropy

   Salvador Hinojosa, D. Oliva, E. Cuevas, M. Perez-Cisneros, and G. Pajares

   2018

   DOI
6. Improving multi-criterion optimization with chaos: a novel Multi-Objective Chaotic Crow Search Algorithm

   Salvador Hinojosa, D. Oliva, E. Cuevas, G. Pajares, O. Avalos, and 1 more author

   Neural Computing and Applications, 2018

   DOI
7. An improved crow search algorithm applied to energy problems

   P. Díaz, M. Pérez-Cisneros, E. Cuevas, O. Avalos, J. Gálvez, and 2 more authors

   Energies, 2018

   DOI
8. Thermal image segmentation using evolutionary computation techniques

   Salvador Hinojosa, G. Pajares, E. Cuevas, and N. Ortega-Sanchez

   In Advances in Soft Computing and Machine Learning in Image Processing, 2018

   DOI
9. A multi-level thresholding method for breast thermograms analysis using Dragonfly algorithm

   Margarita-Arimatea Diaz-Cortes, Noé Ortega-Sánchez, Salvador Hinojosa, Diego Oliva, Erik Cuevas, and 2 more authors

   Infrared Physics & Technology, 2018

   DOI

2017

1. Image segmentation by minimum cross entropy using evolutionary methods

   D. Oliva, Salvador Hinojosa, V. Osuna-Enciso, E. Cuevas, M. Pérez-Cisneros, and 1 more author

   Soft Computing, 2017

   DOI
2. Cross entropy based thresholding for magnetic resonance brain images using Crow Search Algorithm

   D. Oliva, Salvador Hinojosa, E. Cuevas, G. Pajares, O. Avalos, and 1 more author

   Expert Systems with Applications, 2017

   DOI
3. Engineering applications of metaheuristics: An introduction

   D. Oliva, Salvador Hinojosa, and M.V. Demeshko

   2017

   DOI

2014

1. A comparison of evolutionary computation techniques for IIR model identification

   E. Cuevas, J. Gálvez, Salvador Hinojosa, O. Avalos, D. Zaldívar, and 1 more author

   Journal of Applied Mathematics, 2014

   DOI