Publications

J. M. Agulto, Y. L. Noroña, G. C. Gutierrez,E. Benabaye,G. R. Franco, A. F. Laguna, J. W. Cu, J. P. Ilao, M. O. Cordel. Development of a Computer Vision-Based Road Physical Feature Extraction. In Proceeding of the 2023 International Conference on Big Data, Big Data 2023. IEEE,2023. (in Press)

A. Bautista, M. O. Cordel, C. Magpantay, and C. M. Ramos, "A Methodology for Exploring Experiences of Individuals with Tourette Syndrome in Oral and Silent Reading Assessments," 37th The 37th Pacific Asia Conference on Language, Information and Computation (PACLIC 37), (in Press).

A. M. Antioquia and M. O. Cordel, "HAHANet: Towards Accurate Image Classifiers with Less Parameters," PSIVT 2023 - 11th Pacific-Rim Symposium on Image and Video Technology (PSIVT), Image and Video Technology, Lecture Notes in Computer Science, 2023, (in Press)

T. R. Herradura, M. O. Cordel. Exploring the Relationship between EEG Features of Basic and Academic Emotions. Philippine Journal of Science, 2023, 152(4). 

A. B. I. Bernardo, M. O. Cordel, M. O. Calleja, J. M. M. Teves, S. A. Yap, U. C. Chua. Profiling low-proficiency science students in the Philippines using machine learning. Humanit. and soc. sciences commun. 2023, 10(192).  https://doi.org/10.1057/s41599-023-01705-y

A.B.I. Bernardo, M. O. Cordel, M. R. C. Lapinid, J. M. M. Teves, S. A. Yap, U.C. Chua. Contrasting Profiles of Low-Performing Mathematics Students in Public and Private Schools in the Philippines: Insights from Machine Learning. J. Intell. 2022, 10(61). https://doi.org/10.3390/jintelligence10030061

A.B.I. Bernardo, M. O. Cordel, J. G. E. Ricardo, M. A. M. C. Galanza, S. Almonte-Acosta. Global Citizenship Competencies of Filipino Students: Using Machine Learning to Explore the Structure of Cognitive, Affective, and Behavioral Competencies in the 2019 Southeast Asia Primary Learning Metrics. Educ. Sci. 2022, 12(547). https://doi.org/10.3390/educsci12080547

N. P. Del Gallego, J. P. Ilao, M. O. Cordel, and C. P. Ruiz. A new approach for training a physics-based dehazing network using synthetic images. Signal Processing, 199, 2022. https://doi.org/10.1016/j.sigpro.2022.108631

M. E. M. Gonzales, L. C. Uy, J. A. L. Sy and M. O. Cordel, "Distance Metric Recommendation for k-Means Clustering: A Meta-Learning Approach," TENCON 2022 - 2022 IEEE Region 10 Conference (TENCON), 2022, pp. 1-6.  https://doi.org/10.1109/TENCON55691.2022.9978037.

J. V. Chua, J. A. K. Uson, H. K. Moneda and M. O. Cordel, "Balancing Privacy Preservation and Utility in Anti-Face Detection Systems," TENCON 2022 - 2022 IEEE Region 10 Conference TENCON), 2022, pp. 1-6.  https://doi.org/10.1109/TENCON55691.2022.9977834.

A. B. I. Bernardo, M. O. Cordel, R. I. G. Lucas, J. M. M. Teves, S. A. Yap, and U. C. Chua. Using machine learning approaches to explore non-cognitive variables influencing reading proficiency in English among Filipino learners. Education Sciences, 11, 2021. https://doi.org/10.3390/educsci11100628

J. G. Marcelo, G. M. I. Te, M. O. Cordel, and J. P. Ilao. Concealed Objects in a Scene: A Closer Look at the Localization Block of Object Detection Models. In 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2021. https://doi.org/10.1109/ICTAI52525.2021.00172

R. J. D. Reyes, G. V. C. Uy, G. N. D. Minamedez, and M. O. Cordel. Design, Implementation, and Characterization of a Proper Face Mask Usage Classification Model. In 2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP). IEEE, 2021. https://doi.org/10.1109/M2VIP49856.2021.9665103

M. M. F. Pua, J. D. W. Ang Ngo Ching, G. B. B. Betonio, and M. O. Cordel. What Attracts People’s Attention in Banner Advertisements? A Study on Banner Advertisements using a Human Attention Model. In 2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP). IEEE, 2021. https://doi.org/10.1109/M2VIP49856.2021.9665153

C. J. M. Dequito, I. J. L. Dichaves, R. J. G. Juan, M. Y. K. T. Miyanaga, J. P. Ilao, M. O. Cordel, and N. P. A. Del Gallego. Vision-based bicycle and motorcycle detection using a YOLO-based network. Journal of Physics: Conference Series, 1922(1), 2021. https://doi.org/10.1088/1742-6596/1922/1/012003

C. D. Juan, J. R. Bat-Og, Wan K. K., and M. O. Cordel. Investigating Visual Attention-based Traffic Accident Detection Model. Philippine Journal of Science, 150(17), 2021.

N.P. Del Gallego, J.P. Ilao, and M.O. Cordel. Blind First-Order Perspective Distortion Correction Using Parallel Convolutional Neural Networks. Sensors, 20(17), 2020. https://doi.org/10.3390/s20174898

J. G. Marcelo, J. P. Ilao, and M. O. Cordel. Improving Vision-Based Detection of Fruits in a Camouflaged Environment with Deep Neural Networks. In Mechatronics and Machine Vision in Practice 4. Springer Verlag, 2020. https://doi.org/10.1007/978-3-030-43703-9_5

M. O. Cordel. Modeling human attention by learning from large amount of emotional images. In Proceeding of the 2019 International Conference on Big Data, Big Data 2019. IEEE, 2019. https://doi.org/10.1109/BigData47090.2019.9006300

M. O. Cordel, S. Fan, S. Zhiqi, and M. Kankanhalli. Emotion-Aware Human Attention Prediction. In Proceeding of the IEEE/CVF 2019 International Conference on Computer Vision and Pattern Recognition, CVPR 2019. IEEE, 2019. https://doi.org/10.1109/CVPR.2019.00415

M. O. Cordel and A.P. Azcarraga. Characterizing the SOM Feature Detectors under Various Input Conditions. In Advances in Knowledge Discovery and Data Mining . Springer, 2019. https://doi.org/10.1007/978-3-030-16142-2_12

M. O. Cordel and A.P. Azcarraga. A new method for emulating self-organizing maps for visualization of datasets. International Journal of Computational Intelligence and Applications, 17(3), 2018. https://doi.org/10.1142/S1469026818500141

M. O. Cordel and A.P. Azcarraga. Measuring the contribution of filter bank layer to performance of convolutional neural networks. International Journal of Knowledge-Based and Intelligent Engineering Systems, 21(1):15–27, 2017. https://doi.org/10.3233/KES-160343

L. C. De Guzman, R. P. C. Maglaque, V. M. B. Torres, S. P. A. Zapido, and M. O. Cordel. Design and evaluation of a multi-model, multi-level artificial neural network for eczema skin lesion detection. In Al-Dabass D. Bolong N. Hijazi M.H.A., Saad I., editor, Proceedings -AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation, pages 42–47. IEEE, 2016. https://doi.org/10.1109/AIMS.2015.17

T. -C. Lin, K.T. Wong, M. O. Cordel, and J.P. Ilao. Beamforming pointing error of a triaxial velocity sensor under gain uncertainties. Journal of the Acoustical Society of America, 140(3):1675–1685, 2016. https://doi.org/10.1121/1.4962290

J. A. Benolirao, A. J. De Joya, I. Lim, L. K. Osayta, and M. O. Cordel. Quantifying the throughput and latency contribution in secured IEEE 802.15.6 WBAN simulated transmission. In Proceedings - 2016 IEEE Region 10 Symposium, TENSYMP 2016, pages 305–310. IEEE, 2016. https://doi.org/10.1109/TENCONSpring.2016.7519423

C. M. Bautista, C. A. Dy, M. I. Ma ̃nalac, R. A. Orbe, and M. O. Cordel. Convolutional neural network for vehicle detection in low resolution traffic videos. In Proceedings - 2016 IEEE Region 10 Symposium, TENSYMP 2016, pages 277–281. IEEE, 2016. https://doi.org/10.1109/TENCONSpring.2016.7519418

G. P. Melendez and M. O. Cordel. Texture-based detection of lung pathology in chest radiographs using local binary patterns. In BMEiCON 2015 - 8th Biomedical Engineering International Conference. IEEE, 2016. https://doi.org/10.1109/BMEiCON.2015.7399551

M. O. Cordel, A. M. C. Antioquia, and A. P. Azcarraga. Self-organizing maps as feature detectors for supervised neural network pattern recognition. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9950 LNCS:618–625, 2016. https://doi.org/10.1007/978-3-319-46681-1_73

M. O. Cordel and J. P. Ilao. A computer-assisted diagnosis system for the identification/auscultation of pulmonary pathologies. Manila Journal of Science, 9:8–26, 2016.

M. O. Cordel and A.P. Azcarraga. Fast emulation of self-organizing maps for large datasets. In Shakshuki E., editor, Procedia Computer Science, volume 52, pages 381–388. Elsevier B.V., 2015. https://doi.org/10.1016/j.procs.2015.05.002

R. R. G. De La Cruz, T. R. -A. C. Roque, J. D. G. Rosas, C..V. M. Vera Cruz, M. O. Cordel, J. P. Ilao, A. P. J. Rabe, and P. J. Parungao Jr. SMO-based system for identifying common lung conditions using histogram. In International Symposium on Medical Information and Communication Technology, ISMICT, pages 112–116. IEEE, 2013. https://doi.org/10.1109/ISMICT.2013.6521711