65 citations · 221 across the 7 of their papers we have counts for
7 papers
MinkSORT: A 3D deep feature extractor using sparse convolutions to improve 3D multi-object tracking in greenhouse tomato plants
David Rapado-Rincon, Eldert J. van Henten, Gert Kootstra
The agro-food industry is turning to robots to address the challenge of labour shortage. However, agro-food environments pose difficulties for robots due to high variation and occl…
Semantics-Aware Next-best-view Planning for Efficient Search and Detection of Task-relevant Plant Parts
Akshay K. Burusa, Joost Scholten, David Rapado Rincon +3
Searching and detecting the task-relevant parts of plants is important to automate harvesting and de-leafing of tomato plants using robots. This is challenging due to high levels o…
Development and evaluation of automated localisation and reconstruction of all fruits on tomato plants in a greenhouse based on multi-view perception and 3D multi-object tracking
David Rapado Rincon, Eldert J. van Henten, Gert Kootstra
The ability to accurately represent and localise relevant objects is essential for robots to carry out tasks effectively. Traditional approaches, where robots simply capture an ima…
Attention-driven Next-best-view Planning for Efficient Reconstruction of Plants and Targeted Plant Parts
Akshay K. Burusa, Eldert J. van Henten, Gert Kootstra
Robots in tomato greenhouses need to perceive the plant and plant parts accurately to automate monitoring, harvesting, and de-leafing tasks. Existing perception systems struggle wi…
Monitoring and mapping of crop fields with UAV swarms based on information gain
Carlos Carbone, Dario Albani, Federico Magistri +5
Monitoring crop fields to map features like weeds can be efficiently performed with unmanned aerial vehicles (UAVs) that can cover large areas in a short time due to their privileg…
Active learning with MaskAL reduces annotation effort for training Mask R-CNN
Pieter M. Blok, Gert Kootstra, Hakim Elchaoui Elghor +3
The generalisation performance of a convolutional neural network (CNN) is influenced by the quantity, quality, and variety of the training images. Training images must be annotated…
T-LEAP: Occlusion-robust pose estimation of walking cows using temporal information
Helena Russello, Rik van der Tol, Gert Kootstra
As herd size on dairy farms continues to increase, automatic health monitoring of cows is gaining in interest. Lameness, a prevalent health disorder in dairy cows, is commonly dete…