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2020 – today
- 2025
[j4]Pedro Conde
, Rui L. Lopes, Cristiano Premebida:
Improving Accuracy and Calibration of Deep Image Classifiers With Agreement-Driven Dynamic Ensemble. IEEE Open J. Comput. Soc. 6: 164-175 (2025)- 2024
- [j3]Tiago Barros, Luís Garrote, Pedro Conde, Matthew J. Coombes, Cunjia Liu, Cristiano Premebida, Urbano J. Nunes:
PointNetPGAP-SLC: A 3D LiDAR-Based Place Recognition Approach With Segment-Level Consistency Training for Mobile Robots in Horticulture. IEEE Robotics Autom. Lett. 9(11): 10471-10478 (2024) - [i5]Tiago Barros, Luís Garrote, Pedro Conde, Matthew Coombes, C. Liu, Cristiano Premebida, Urbano J. Nunes:
PointNetPGAP-SLC: A 3D LiDAR-based Place Recognition Approach with Segment-level Consistency Training for Mobile Robots in Horticulture. CoRR abs/2405.19038 (2024) - 2023
- [j2]Gledson Melotti, Weihao Lu, Pedro Conde, Dezong Zhao, Alireza Asvadi, Nuno Gonçalves, Cristiano Premebida:
Probabilistic Approach for Road-Users Detection. IEEE Trans. Intell. Transp. Syst. 24(9): 9253-9267 (2023) - [c2]Pedro Conde, Tiago Barros, Cristiano Premebida, Urbano J. Nunes:
ECE-based Deep Ensemble for Neural Network Calibration in Satellite Image Classification. ICARSC 2023: 50-55 - [i4]Tiago Barros, Luis Garrote, Pedro Conde, Matthew Coombes, C. Liu, Cristiano Premebida, Urbano J. Nunes:
ORCHNet: A Robust Global Feature Aggregation approach for 3D LiDAR-based Place recognition in Orchards. CoRR abs/2303.00477 (2023) - [i3]Pedro Conde, Tiago Barros, Rui L. Lopes, Cristiano Premebida, Urbano J. Nunes:
Approaching Test Time Augmentation in the Context of Uncertainty Calibration for Deep Neural Networks. CoRR abs/2304.05104 (2023) - [i2]Pedro Conde, Rui L. Lopes, Cristiano Premebida:
A Theoretical and Practical Framework for Evaluating Uncertainty Calibration in Object Detection. CoRR abs/2309.00464 (2023) - 2022
- [j1]Tiago Barros, Pedro Conde, Gil Gonçalves, Cristiano Premebida, Miguel Monteiro, Carla Sofia Santos Ferreira, Urbano J. Nunes:
Multispectral vineyard segmentation: A deep learning comparison study. Comput. Electron. Agric. 195: 106782 (2022) - [c1]Pedro Conde, Cristiano Premebida:
Adaptive-TTA: accuracy-consistent weighted test time augmentation method for the uncertainty calibration of deep learning classifiers. BMVC 2022: 869 - 2021
- [i1]Tiago Barros, Pedro Conde, Gil Gonçalves, Cristiano Premebida, Miguel Monteiro, Carla Sofia Santos Ferreira, Urbano J. Nunes:
Multispectral Vineyard Segmentation: A Deep Learning approach. CoRR abs/2108.01200 (2021)
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