| Android malware detection through hybrid features fusion and ensemble classifiers: The AndroPyTool framework and the OmniDroid dataset A Martín, R Lara-Cabrera, D Camacho Information Fusion 52, 128-142, 2019 | 167 | 2019 |
| EvoDeep: a new Evolutionary approach for automatic Deep Neural Networks parametrisation A Martín, R Lara-Cabrera, F Fuentes-Hurtado, V Naranjo, D Camacho Journal of Parallel and Distributed Computing, 2018 | 103 | 2018 |
| MOCDroid: multi-objective evolutionary classifier for Android malware detection A Martín, HD Menéndez, D Camacho Soft Computing 21 (24), 7405-7415, 2016 | 91 | 2016 |
| CANDYMAN: Classifying Android malware families by modelling dynamic traces with Markov chains A Martín, V Rodríguez-Fernández, D Camacho Engineering Applications of Artificial Intelligence 74, 121-133, 2018 | 84 | 2018 |
| Picking on the family: Disrupting android malware triage by forcing misclassification A Calleja, A Martín, HD Menéndez, J Tapiador, D Clark Expert Systems with Applications 95, 113-126, 2018 | 63 | 2018 |
| Evolving deep neural networks architectures for android malware classification A Martín, F Fuentes-Hurtado, V Naranjo, D Camacho 2017 IEEE Congress on Evolutionary Computation (CEC), 1659-1666, 2017 | 52 | 2017 |
| FacTeR-Check: Semi-automated fact-checking through semantic similarity and natural language inference A Martín, J Huertas-Tato, Á Huertas-García, G Villar-Rodríguez, ... Knowledge-based systems 251, 109265, 2022 | 51 | 2022 |
| ADROIT: Android malware detection using meta-information A Martín, A Calleja, HD Menéndez, J Tapiador, D Camacho 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016 | 43 | 2016 |
| Fusing CNNs and statistical indicators to improve image classification J Huertas-Tato, A Martín, J Fierrez, D Camacho Information Fusion 79, 174-187, 2022 | 41 | 2022 |
| Optimising convolutional neural networks using a hybrid statistically-driven coral reef optimisation algorithm A Martín, VM Vargas, PA Gutiérrez, D Camacho, C Hervás-Martínez Applied Soft Computing 90, 106144, 2020 | 39 | 2020 |
| A Framework for User Adaptation and Profiling for Social Robotics in Rehabilitation A Martín, JC Pulido, JC González, Á García-Olaya, C Suárez Sensors 20 (17), 4792, 2020 | 28 | 2020 |
| A new tool for static and dynamic Android malware analysis A Martín, R Lara-Cabrera, D Camacho Data Science and Knowledge Engineering for Sensing Decision Support …, 2018 | 28 | 2018 |
| An in-depth study of the jisut family of android ransomware A Martín, J Hernandez-Castro, D Camacho IEEE Access 6, 57205-57218, 2018 | 27 | 2018 |
| Evolving Generative Adversarial Networks to improve image steganography A Martín, A Hernández, M Alazab, J Jung, D Camacho Expert Systems with Applications 222, 119841, 2023 | 26 | 2023 |
| Countering misinformation through semantic-aware multilingual models Á Huertas-García, J Huertas-Tato, A Martín, D Camacho International conference on intelligent data engineering and automated …, 2021 | 23 | 2021 |
| SILT: Efficient transformer training for inter-lingual inference J Huertas-Tato, A Martín, D Camacho Expert Systems with Applications 200, 116923, 2022 | 20* | 2022 |
| Genetic boosting classification for malware detection A Martin, HD Menéndez, D Camacho 2016 IEEE Congress on Evolutionary Computation (CEC), 1030-1037, 2016 | 20 | 2016 |
| String-based malware detection for android environments A Martín, HD Menéndez, D Camacho Intelligent Distributed Computing X: Proceedings of the 10th International …, 2017 | 19 | 2017 |
| Virality, only the tip of the iceberg: ways of spread and interaction around COVID-19 misinformation in Twitter G Villar-Rodríguez, M Souto-Rico, A Martín Communication & Society, 239-256, 2022 | 13 | 2022 |
| Profiling Hate Speech Spreaders on Twitter: Transformers and mixed pooling. Á Huertas-García, J Huertas-Tato, A Martín, D Camacho CLEF (Working Notes) 2021, 2021 | 12 | 2021 |
David CamachoUniversidad Politécnica de MadridVerified email at upm.es
