Andres Milioto

Orcid: 0000-0002-5716-3279

According to our database1, Andres Milioto authored at least 28 papers between 2018 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2022
OverlapNet: a siamese network for computing LiDAR scan similarity with applications to loop closing and localization.
Auton. Robots, 2022

2021
Efficient Semantic Scene Understanding for Mobile Robots.
PhD thesis, 2021

Building an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution.
IEEE Robotics Autom. Mag., 2021

Deep Compression for Dense Point Cloud Maps.
IEEE Robotics Autom. Lett., 2021

Joint Plant Instance Detection and Leaf Count Estimation for In-Field Plant Phenotyping.
IEEE Robotics Autom. Lett., 2021

Towards 3D LiDAR-based semantic scene understanding of 3D point cloud sequences: The SemanticKITTI Dataset.
Int. J. Robotics Res., 2021

Improving Monocular Depth Estimation by Semantic Pre-training.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

A Benchmark for LiDAR-based Panoptic Segmentation based on KITTI.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020
Robust joint stem detection and crop-weed classification using image sequences for plant-specific treatment in precision farming.
J. Field Robotics, 2020

Classifying Obstacles and Exploiting Class Information for Humanoid Navigation Through Cluttered Environments.
Int. J. Humanoid Robotics, 2020

OverlapNet: Loop Closing for LiDAR-based SLAM.
Proceedings of the Robotics: Science and Systems XVI, 2020

LiDAR Panoptic Segmentation for Autonomous Driving.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Gradient and Log-based Active Learning for Semantic Segmentation of Crop and Weed for Agricultural Robots.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019
Building an Aerial-Ground Robotics System for Precision Farming.
CoRR, 2019

A Dataset for Semantic Segmentation of Point Cloud Sequences.
CoRR, 2019

RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

SuMa++: Efficient LiDAR-based Semantic SLAM.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics using CNNs.
Proceedings of the International Conference on Robotics and Automation, 2019

Fast Instance and Semantic Segmentation Exploiting Local Connectivity, Metric Learning, and One-Shot Detection for Robotics.
Proceedings of the International Conference on Robotics and Automation, 2019

SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018
Fully Convolutional Networks With Sequential Information for Robust Crop and Weed Detection in Precision Farming.
IEEE Robotics Autom. Lett., 2018

Geometrical Stem Detection from Image Data for Precision Agriculture.
CoRR, 2018

Joint Stem Detection and Crop-Weed Classification for Plant-Specific Treatment in Precision Farming.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Ocean Eddy Identification and Tracking Using Neural Networks.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Real-Time Semantic Segmentation of Crop and Weed for Precision Agriculture Robots Leveraging Background Knowledge in CNNs.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Classifying Obstacles and Exploiting Knowledge About Classes for Efficient Humanoid Navigation.
Proceedings of the 18th IEEE-RAS International Conference on Humanoid Robots, 2018


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