| MOCDroid: multi-objective evolutionary classifier for Android malware detection A Martín, HD Menéndez, D Camacho Soft Computing 21 (24), 7405-7415, 2017 | 50 | 2017 |
| 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 | 40 | 2018 |
| 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 | 33 | 2019 |
| 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 | 30 | 2018 |
| 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 | 27 | 2018 |
| 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 | 24 | 2016 |
| 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 | 22 | 2017 |
| Genetic boosting classification for malware detection A Martin, HD Menéndez, D Camacho 2016 IEEE Congress on Evolutionary Computation (CEC), 1030-1037, 2016 | 17 | 2016 |
| String-based malware detection for android environments A Martín, HD Menéndez, D Camacho International Symposium on Intelligent and Distributed Computing, 99-108, 2016 | 15 | 2016 |
| 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 | 9 | 2020 |
| Therapy monitoring and patient evaluation with social robots A Martín, JC González, JC Pulido, Á García-Olaya, F Fernández, ... Proceedings of the 3rd 2015 Workshop on ICTs for Improving Patients …, 2015 | 9 | 2015 |
| 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, 509-516, 2018 | 7 | 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 | 5 | 2018 |
| Studying the influence of static api calls for hiding malware A Martín, HD Menéndez, D Camacho Conference of the Spanish Association for Artificial Intelligence, 363-372, 2016 | 5 | 2016 |
| 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 | 3 | 2020 |
| Cloud type identification using data fusion and ensemble learning J Huertas-Tato, A Martín, D Camacho International Conference on Intelligent Data Engineering and Automated …, 2020 | 1 | 2020 |
| Statistically-driven Coral Reef metaheuristic for automatic hyperparameter setting and architecture design of Convolutional Neural Networks A Martin, R Lara-Cabrera, VM Vargas, PA Gutiérrez, C Hervás-Martínez, ... 2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020 | 1 | 2020 |
| Evolving the Architecture and Hyperparameters of DNNs for Malware Detection A Martín, D Camacho Deep Neural Evolution, 357-377, 2020 | 1 | 2020 |
| Fusion of CNNs and statistical indicators to improve image classification J Huertas-Tato, A Martín, J Fierrez, D Camacho arXiv preprint arXiv:2012.11049, 2020 | | 2020 |
| Evolving the Architecture and Hyperparameters of DNNs A Martín, D Camacho Deep Neural Evolution: Deep Learning with Evolutionary Computation, 357, 2020 | | 2020 |
David CamachoUniversidad Politécnica de MadridVerified email at upm.es
