18 citations · 38 across the 4 of their papers we have counts for
4 papers
Exploiting Object-based and Segmentation-based Semantic Features for Deep Learning-based Indoor Scene Classification
Ricardo Pereira, Luís Garrote, Tiago Barros +2
Indoor scenes are usually characterized by scattered objects and their relationships, which turns the indoor scene classification task into a challenging computer vision task. Desp…
A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification
Ricardo Pereira, Tiago Barros, Luis Garrote +2
This work proposes a novel approach that uses a semantic segmentation mask to obtain a 2D spatial layout of the segmentation-categories across the scene, designated by segmentation…
Place recognition survey: An update on deep learning approaches
Tiago Barros, Ricardo Pereira, Luís Garrote +2
Autonomous Vehicles (AV) are becoming more capable of navigating in complex environments with dynamic and changing conditions. A key component that enables these intelligent vehicl…
AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognition
Tiago Barros, Luís Garrote, Ricardo Pereira +2
LiDAR-based place recognition is one of the key components of SLAM and global localization in autonomous vehicles and robotics applications. With the success of DL approaches in le…