11 citations · 17 across the 5 of their papers we have counts for
5 papers
PointRAFT: 3D deep learning for high-throughput prediction of potato tuber weight from partial point clouds
Pieter M. Blok, Haozhou Wang, Hyun Kwon Suh +3
Potato yield is a key indicator for optimizing cultivation practices in agriculture. Potato yield can be estimated on harvesters using RGB-D cameras, which capture three-dimensiona…
DistillFSS: Synthesizing Few-Shot Knowledge into a Lightweight Segmentation Model
Pasquale De Marinis, Pieter M. Blok, Uzay Kaymak +3
Cross-Domain Few-Shot Semantic Segmentation (CD-FSS) seeks to segment unknown classes in unseen domains using only a few annotated examples. This setting is inherently challenging:…
High-throughput 3D shape completion of potato tubers on a harvester
Pieter M. Blok, Federico Magistri, Cyrill Stachniss +3
Potato yield is an important metric for farmers to further optimize their cultivation practices. Potato yield can be estimated on a harvester using an RGB-D camera that can estimat…
Active learning for efficient annotation in precision agriculture: a use-case on crop-weed semantic segmentation
Bart M. van Marrewijk, Charbel Dandjinou, Dan Jeric Arcega Rustia +5
Optimizing deep learning models requires large amounts of annotated images, a process that is both time-intensive and costly. Especially for semantic segmentation models in which e…
DODA: Adapting Object Detectors to Dynamic Agricultural Environments in Real-Time with Diffusion
Shuai Xiang, Pieter M. Blok, James Burridge +2
Object detection has wide applications in agriculture, but domain shifts of diverse environments limit the broader use of the trained models. Existing domain adaptation methods usu…