Publications

Mendes, M. B., Farinha, D., Oliveira, P., Barroso, J. M., Rato, L. M., Sousa, A., & Rato, A. E. (2025). The use of Sentinel 2 to quantify N, Ca, and K in walnut orchards. Computers and Electronics in Agriculture, 229, 109763. https://doi.org/10.1016/j.compag.2024.109763

Lasker, A., Ghosh, M., Sk, M. O., Gonçalves, T., Chakraborty, C., & Roy, K. (2026). LungConVT-Net: A visual transformer network with blended features for Pneumonia detection. Pattern Recognition, 171, 112150. https://doi.org/10.1016/j.patcog.2025.112150

Yang, H., & Gonçalves, T. (2025). MultiLTR: Text Ranking with a Multi-Stage Learning-to-Rank Approach. Information, 16(4), 308. https://doi.org/10.3390/info16040308

Saias, J. (2025). Advances in NLP Techniques for Detection of Message-Based Threats in Digital Platforms: A Systematic Review. Electronics, 14(13), 2551. https://doi.org/10.3390/electronics14132551

Tereso, M., Gonçalves, T., & Rato, L. (2025). Automatic defect detection in ornamental rocks. IbPRIA 2025: 12th Iberian Conference on Pattern Recognition and Image Analysis. http://dx.doi.org/10.13140/RG.2.2.35449.17760

Santos, D., Miquelina, N., Schmidt, D., Quaresma, P., & Nogueira, V. B. (2025). Performance Evaluation of NLP Models for European Portuguese: Multi-GPU/Multi-node Configurations and Optimization Techniques. In T. Zhu, J. Li, & A. Castiglione (Eds.), Algorithms and Architectures for Parallel Processing (pp. 298–314). Springer, Singapore. https://doi.org/10.1007/978-981-96-1551-3_20

Gamallo, P., Rodríguez, P., Santos, D., Sotelo, S., Miquelina, N., Paniagua, S., Schmidt, D., de-Dios-Flores, I., Quaresma, P., Bardanca, D., Pichel, J. R., Nogueira, V., & Barro, S. (2025). A Galician-Portuguese Generative Model. In M. F. Santos, J. Machado, P. Novais, P. Cortez, & P. M. Moreira (Eds.), Progress in Artificial Intelligence (pp. 292–304). Springer, Cham. https://doi.org/10.1007/978-3-031-73503-5_24

Borrecho, G., Rato, L., Salgueiro, P., Ferreira, I., Madeira, C., & Oliveira, R. (2025). PathProfiler as a Quantitative Quality Control Software for Prostate Biopsies – Pilot Study in Centro de Anatomia Patológica Germano de Sousa. ECDP2025 21st European Congress on Digital Pathology. http://dx.doi.org/10.13140/RG.2.2.28371.28960

Yang, H., Li, S., & Gonçalves, T. (2024). Enhancing Biomedical Question Answering with Large Language Models. Information, 15(8), 494. doi: 10.3390/info15080494

Rahman, M., Sarwar, H., Kader, M. A., Gonçalves, T., & Tin, T. T. (2024). Review and Empirical Analysis of Machine Learning-Based Software Effort Estimation. IEEE Access, 12, 85661-85680. doi: 10.1109/ACCESS.2024.3404879

Lasker, A., Ghosh, M., Das, S., Obaidullah, S. M., Chakraborty, C., Goncalves, T., & Roy, K. (2024). Segmented-Based and Segmented-Free Approach for COVID-19 Detection. In K. Dasgupta et al. (Eds.), Computational Intelligence in Communications and Business Analytics (Vol. 1956). Springer, Cham. doi: 10.1007/978-3-031-48879-5_25

Saias, J., & Bravo, J. (2024). Sensor-Based Real-Time Monitoring Approach for Multi-Participant Workout Intensity Management. Electronics, 13(18), 3687. doi: 10.3390/electronics13183687

Pereira, J. L. M., Fonseca, M. J., Lopes, A., & Galhardas, H. (2024). Cleenex: Support for User Involvement during an Iterative Data Cleaning Process. ACM Journal of Data and Information Quality, 16(1), 1-26. doi: 10.1145/3648476

Lamar Léon, J., Salgueiro, P., Gonçalves, T., & Rato, L. (2024). EIF-SlideWindow: Enhancing Simultaneous Localization and Mapping Efficiency and Accuracy with a Fixed-Size Dynamic Information Matrix. Big Data and Cognitive Computing, 8(12), 193. https://doi.org/10.3390/bdcc8120193

Yang, H., & Gonçalves, T. (2024). Improving Consumer Health Search with Field-Level Learning-to-Rank Techniques. Information, 15(11), 695. https://doi.org/10.3390/info15110695

Yang, H., & Gonçalves, T. (2023). Field features: The impact in learning to rank approaches. Applied Soft Computing, 138. doi: 10.1016/j.asoc.2023.110183

Vijithananda, S. et al. (2023). Discriminating Malignant and Benign Brain Tumors Using Texture Features of MRI-ADC Images. Multidiscip Cancer Investig, 7(1), 17-26. mcijournal.com/article-1-365-en.html

Medeiros, E., Corado, L., Rato, L., & Quaresma, P. (2023). Domain Adaptation Speech-to-Text for Low-Resource European Portuguese Using Deep Learning. Future Internet, 15(5), 159. doi: 10.3390/fi15050159

Teimas, R., & Saias, J. (2023). Detecting Persuasion Attempts on Social Networks. Electronics, 12(21), 4447. mdpi.com/2079-9292/12/21/4447

Rahman, M., Gonçalves, T., & Sarwar, H. (2023). Review of Existing Datasets Used for Software Effort Estimation. International Journal of Advanced Computer Science and Applications, 14(7). doi: 10.14569/IJACSA.2023.01407100

Vijithananda, S. M., Jayatilake, M. L., & Gonçalves, T. (2023). Texture Feature Analysis of MRI-ADC Images to Differentiate Glioma Grades. Scientific Reports, 13, 15772. doi: 10.1038/s41598-023-41353-5

Rahman, M., Roy, P. P., & Gonçalves, T. (2023). Software Effort Estimation Using Machine Learning Technique. International Journal of Advanced Computer Science and Applications, 14(4). doi: 10.14569/IJACSA.2023.0140491

Ghosh, S., Gonçalves, T., & Das, N. (2023). Im2Graph: A Weakly Supervised Approach for Generating Holistic Scene Graphs. Future Internet, 15(2), 70. doi: 10.3390/fi15020070

Gonçalves, T., Veladas, R., Yang, H., Vieira, R., & Quaresma, P. (2023). Clinical Screening Prediction in the Portuguese NHS. Future Internet, 15(1), 26. doi: 10.3390/fi15010026

Blom, B., & Pereira, J. L. (2023, November). Domain Adaptation in Transformer Models: Question Answering of Dutch Government Policies. In International Conference on Intelligent Data Engineering. Springer, Cham. link.springer.com/chapter/10.1007/978-3-031-48232-8_19

Pereira, J. L. M. (2023). Towards Effective and Effortless Data Cleaning. scholar.tecnico.ulisboa.pt/records/_9Wa_izOSPFA-ckoVSS5LrcEVDX-bgdZWHYy

Infante, P., Jacinto, G., Afonso, A., Rego, L., Nogueira, P., Silva, M., Nogueira, V., Saias, J., Quaresma, P., Santos, D., et al. (2023). Factors That Influence the Type of Road Traffic Accidents: A Case Study in a District of Portugal. Sustainability, 15(3), 2352. doi: 10.3390/su15032352

Nogueira, P., Silva, M., Infante, P., Nogueira, V., Manuel, P., Afonso, A., Jacinto, G., Rego, L., Quaresma, P., Saias, J., et al. (2023). Learning from Accidents: Spatial Intelligence Applied to Road Accidents with Insights from a Case Study in Setúbal District, Portugal. ISPRS International Journal of Geo-Information, 12(3), 93. doi: 10.3390/ijgi12030093

Infante, P., Jacinto, G., Santos, D., Nogueira, P., Afonso, A., Quaresma, P., Silva, M., Nogueira, V., Rego, L., Saias, J., et al. (2023). Prediction of Road Traffic Accidents on a Road in Portugal: A Multidisciplinary Approach Using Artificial Intelligence, Statistics, and Geographic Information Systems. Information, 14(4), 238. doi: 10.3390/info14040238

Obaidullah, S. M., Mukherjee, H., & Gonçalves, T. (2022). Mammogram Mass Classification: A CNN-Based Technique Applied to Different Age Groups. In K. Santosh, R. Hegadi, & U. Pal (Eds.), Recent Trends in Image Processing and Pattern Recognition (Vol. 1576). Springer, Cham. doi: 10.1007/978-3-031-07005-1_11

Dhar, A., Mukherjee, H., Sen, S., Sk, M. O., Biswas, A., Gonçalves, T., & Roy, K. (2022). Author Identification from Literary Articles with Visual Features: A Case Study with Bangla Documents. Future Internet, 14(10), 272. doi: 10.3390/fi14100272

Li, H., Barão, M., Rato, L., & Wen, S. (2022). HMM-Based Dynamic Mapping with Gaussian Random Fields. Electronics, 11(5), 722. doi: 10.3390/electronics11050722

Saias, J., & Rato, L., & Gonçalves, T. (2022). An Approach to Churn Prediction for Cloud Services Recommendation and User Retention. Information, 13(5), 227. doi: 10.3390/info13050227

Raiyani, K., Gonçalves, T., & Rato, L. (2022). Abbreviating Labeling Cost for Sentinel-2 Image Scene Classification Through Active Learning. In A. J. Pinho, P. Georgieva, L. F. Teixeira, & J. A. Sánchez (Eds.), Pattern Recognition and Image Analysis (Vol. 13256). Springer, Cham. doi: 10.1007/978-3-031-04881-4_24

Yang, H., Gonçalves, T., Quaresma, P., Vieira, R., Veladas, R., Pinto, C. S., Oliveira, J., Ferreira, M. C., Morais, J., & Pereira, A. R. (2022). Clinical Trial Classification of SNS24 Calls with Neural Networks. Future Internet, 14(5), 130. doi: 10.3390/fi14050130

Lasker, A., Ghosh, M., Obaidullah, S. M., Chakraborty, C., Gonçalves, T., & Roy, K. (2022). Ensemble Stack Architecture for Lungs Segmentation from X-ray Images. In H. Yin, D. Camacho, & P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022 (Vol. 13756). Springer, Cham. doi: 10.1007/978-3-031-21753-1_1

Vijithananda, S. M., Jayatilake, M. L., Hewavithana, B., Gonçalves, T., & Rato, L. (2022). Feature Extraction from MRI ADC Images for Brain Tumor Classification Using Machine Learning Techniques. BioMed Eng Online, 21, 52. doi: 10.1186/s12938-022-01022-6

Raiyani, K., Gonçalves, T., Rato, L., & Barão, M. (2022). Mahalanobis Distance-Based Accuracy Prediction Models for Sentinel-2 Image Scene Classification. International Journal of Remote Sensing, 43(15–16), 6001-6026. doi: 10.1080/01431161.2021.2013575

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