AVEC 2016: Depression, Mood, and Emotion Recognition Workshop and Challenge M Valstar, J Gratch, B Schuller, F Ringeval, D Lalanne, M Torres Torres, ... Proceedings of the 6th International Workshop on Audio/Visual Emotion …, 2016 | 730 | 2016 |
Chalearn looking at people and faces of the world: Face analysis workshop and challenge 2016 S Escalera, M Torres Torres, B Martinez, X Baró, H Jair Escalante, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 133 | 2016 |
The NoXi database: multimodal recordings of mediated novice-expert interactions A Cafaro, J Wagner, T Baur, S Dermouche, M Torres Torres, C Pelachaud, ... Proceedings of the 19th ACM International Conference on Multimodal …, 2017 | 116 | 2017 |
A hybrid deep learning approach for driver distraction detection JM Mase, P Chapman, GP Figueredo, MT Torres 2020 International Conference on Information and Communication Technology …, 2020 | 75 | 2020 |
Evaluating the impact of Heavy Goods Vehicle driver monitoring and coaching to reduce risky behaviour JM Mase, S Majid, M Mesgarpour, MT Torres, GP Figueredo, P Chapman Accident Analysis & Prevention 146, 105754, 2020 | 46 | 2020 |
Benchmarking deep learning models for driver distraction detection J Mafeni Mase, P Chapman, GP Figueredo, M Torres Torres Machine Learning, Optimization, and Data Science: 6th International …, 2020 | 36 | 2020 |
Text data augmentations: Permutation, antonyms and negation G Haralabopoulos, MT Torres, I Anagnostopoulos, D McAuley Expert Systems with Applications 177, 114769, 2021 | 33 | 2021 |
Feature importance in machine learning models: A fuzzy information fusion approach D Rengasamy, JM Mase, A Kumar, B Rothwell, MT Torres, MR Alexander, ... Neurocomputing 511, 163-174, 2022 | 28 | 2022 |
Galaxy image classification based on citizen science data: A comparative study M Jimenez, MT Torres, R John, I Triguero IEEE Access 8, 47232-47246, 2020 | 26 | 2020 |
Automatic habitat classification using image analysis and random forest M Torres, G Qiu Ecological Informatics 23, 126-136, 2014 | 22 | 2014 |
RevManHAL: towards automatic text generation in systematic reviews M Torres Torres, CE Adams Systematic reviews 6, 1-7, 2017 | 20 | 2017 |
Capturing Uncertainty in Heavy Goods Vehicles Driving Behaviour JM Mase, U Agrawal, D Pekaslan, M Mesgarpour, P Chapman, MT Torres, ... 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 18 | 2020 |
Automatic Neonatal Pain Estimation: An Acute Pain in Neonates Database J Egede, M Valstar, MT Torres, D Sharkey 2019 8th International Conference on Affective Computing and Intelligent …, 2019 | 18 | 2019 |
AutoRoot: open-source software employing a novel image analysis approach to support fully-automated plant phenotyping MP Pound, S Fozard, M Torres Torres, BG Forde, AP French Plant methods 13 (1), 1-10, 2017 | 17 | 2017 |
AVEC 2016-Depression M Valstar, J Gratch, B Schuller, F Ringeval, D Lalanne, MT Torres, ... Mood, and Emotion Recognition Workshop and Challenge, 2016 | 15 | 2016 |
Postnatal gestational age estimation of newborns using Small Sample Deep Learning MT Torres, M Valstar, C Henry, C Ward, D Sharkey Image and vision computing 83, 87-99, 2019 | 14 | 2019 |
Evaluation of synthetic aerial imagery using unconditional generative adversarial networks M Yates, G Hart, R Houghton, MT Torres, M Pound ISPRS Journal of Photogrammetry and Remote Sensing 190, 231-251, 2022 | 13 | 2022 |
Small sample deep learning for newborn gestational age estimation MT Torres, MF Valstar, C Henry, C Ward, D Sharkey 2017 12th IEEE International Conference on Automatic Face & Gesture …, 2017 | 13 | 2017 |
Objective assessment of subjective tasks in crowdsourcing applications G Haralabopoulos, M Tsikandilakis, MT Torres, D McAuley | 12 | 2020 |
L2AE-D: Learning to aggregate embeddings for few-shot learning with meta-level dropout H Song, MT Torres, E Özcan, I Triguero Neurocomputing 442, 200-208, 2021 | 11 | 2021 |