Search Results for author:
Found 7 papers, 5 papers with code
Least Squares Optimization: from Theory to Practice
In this work, we propose a unified methodology to design and develop efficient Least-Squares Optimization algorithms, focusing on the structures and patterns of each specific domain.
Robotics
Plug-and-Play SLAM: A Unified SLAM Architecture for Modularity and Ease of Use
Nowadays, SLAM (Simultaneous Localization and Mapping) is considered by the Robotics community to be a mature field.
Robotics
Robust Double-Encoder Network for RGB-D Panoptic Segmentation
We propose a novel encoder-decoder neural network that processes RGB and depth separately through two encoders.
IR-MCL: Implicit Representation-Based Online Global Localization
The experiments suggest that the presented implicit representation is able to predict more accurate 2D LiDAR scans leading to an improved observation model for our particle filter-based localization.
Hierarchical Approach for Joint Semantic, Plant Instance, and Leaf Instance Segmentation in the Agricultural Domain
In this paper, we address the problem of joint semantic, plant instance, and leaf instance segmentation of crop fields from RGB data.
On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural Robotics
Furthermore, the pre-trained networks obtain similar performance to the fully supervised with less labeled data.
Unsupervised Pre-Training for 3D Leaf Instance Segmentation
Monitoring plants and measuring their traits is an important task in agriculture often referred to as plant phenotyping.
