| SARS-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification E Soares, P Angelov, S Biaso, MH Froes, DK Abe MedRxiv, 2020 | 527 | 2020 |
| Explainable artificial intelligence: an analytical review PP Angelov, EA Soares, R Jiang, NI Arnold, PM Atkinson Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 11 (5 …, 2021 | 507 | 2021 |
| Towards explainable deep neural networks (xDNN) P Angelov, E Soares Neural Networks 130, 185-194, 2020 | 292 | 2020 |
| Harnessing the power of smart and connected health to tackle COVID-19: IoT, AI, robotics, and blockchain for a better world F Firouzi, B Farahani, M Daneshmand, K Grise, J Song, R Saracco, ... IEEE Internet of Things Journal 8 (16), 12826-12846, 2021 | 112 | 2021 |
| Ensemble of evolving data clouds and fuzzy models for weather time series prediction E Soares, P Costa Jr, B Costa, D Leite Applied Soft Computing 64, 445-453, 2018 | 110 | 2018 |
| Artificial intelligence in automated sorting in trash recycling BS Costa, ACS Bernardes, JVA Pereira, VH Zampa, VA Pereira, GF Matos, ... Anais do XV Encontro Nacional de Inteligência Artificial e Computacional …, 2018 | 73 | 2018 |
| A self‐adaptive synthetic over‐sampling technique for imbalanced classification X Gu, PP Angelov, EA Soares International Journal of Intelligent Systems 35 (6), 923-943, 2020 | 50 | 2020 |
| Explainable-by-design approach for covid-19 classification via ct-scan P Angelov, E Soares | 49 | 2020 |
| Explaining deep learning models through rule-based approximation and visualization E Soares, PP Angelov, B Costa, MPG Castro, S Nageshrao, D Filev IEEE Transactions on Fuzzy Systems 29 (8), 2399-2407, 2020 | 45 | 2020 |
| Autonomous learning multiple-model zero-order classifier for heart sound classification E Soares, P Angelov, X Gu Applied Soft Computing 94, 106449, 2020 | 37 | 2020 |
| SARS-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification. medRxiv 2020 E Soares, P Angelov, S Biaso, MH Froes, DK Abe Google Scholar, 0 | 25 | |
| Fair-by-design explainable models for prediction of recidivism E Soares, P Angelov arXiv preprint arXiv:1910.02043, 2019 | 23 | 2019 |
| Incremental gaussian granular fuzzy modeling applied to hurricane track forecasting EA Soares, HA Camargo, SJ Camargo, DF Leite 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2018 | 19 | 2018 |
| Actively semi-supervised deep rule-based classifier applied to adverse driving scenarios E Soares, P Angelov, B Costa, M Castro 2019 international joint conference on neural networks (IJCNN), 1-8, 2019 | 18 | 2019 |
| A large dataset of real patients CT scans for COVID-19 identification E Soares, P Angelov Harv. Dataverse 1, 2020 | 17 | 2020 |
| Explainable density-based approach for self-driving actions classification E Soares, P Angelov, D Filev, B Costa, M Castro, S Nageshrao 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 16 | 2019 |
| Towards deep machine reasoning: a prototype-based deep neural network with decision tree inference P Angelov, E Soares 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | 14 | 2020 |
| SARS-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification. medRxiv E Soares, P Angelov, S Biaso, MH Froes, DK Abe New Haven, CT, USA 10 (2020.04), 24.20078584, 2020 | 14 | 2020 |
| Self-organising and self-learning model for soybean yield prediction M Alghamdi, P Angelov, R Gimenez, M Rufino, E Soares 2019 Sixth International Conference on Social Networks Analysis, Management …, 2019 | 11 | 2019 |
| Detecting and learning from unknown by extremely weak supervision: exploratory classifier (xClass) P Angelov, E Soares Neural Computing and Applications 33 (22), 15145-15157, 2021 | 10* | 2021 |
Plamen P AngelovChair Professor in Intelligent Systems, School of Computing and Communications, Lancaster University在 lancaster.ac.uk 的电子邮件经过验证
