Search Results for author: P. Conde

Found 3 papers, 2 papers with code

ORCHNet: A Robust Global Feature Aggregation approach for 3D LiDAR-based Place recognition in Orchards

1 code implementation1 Mar 2023 T. Barros, L. Garrote, P. Conde, M. J. Coombes, C. Liu, C. Premebida, U. J. Nunes

In this work, we address the place recognition problem in orchards resorting to 3D LiDAR data, which is considered a key modality for robustness.

Loop Closure Detection

Probabilistic Approach for Road-Users Detection

no code implementations2 Dec 2021 G. Melotti, W. Lu, P. Conde, D. Zhao, A. Asvadi, N. Gonçalves, C. Premebida

It is demonstrated that the proposed technique reduces overconfidence in the false positives without degrading the performance on the true positives.

Autonomous Driving Object +2

Multispectral Vineyard Segmentation: A Deep Learning approach

1 code implementation2 Aug 2021 T. Barros, P. Conde, G. Gonçalves, C. Premebida, M. Monteiro, C. S. S. Ferreira, U. J. Nunes

In this work, a study is presented of semantic segmentation for vine detection in real-world vineyards by exploring state-of-the-art deep segmentation networks and conventional unsupervised methods.

Segmentation Semantic Segmentation

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