11 citations · 22 across the 9 of their papers we have counts for
6 papers · 1 filter
Semantics-Guided Multimodal Masked Autoencoder Pretraining for 3D BEV Object Detection
Prabuddhi Wariyapperuma, Rajitha de Silva, Marc Hanheide +2
Accurate 3D bird's-eye view (BEV) object detection is essential for autonomous driving, and depends strongly on effective multimodal representations from complementary sensors such…
Calibration-Informative Region Selection for Online LiDAR--Camera Calibration in Agricultural Environments
Rajitha de Silva, Grzegorz Cielniak
Reliable multi-modal calibration requires identifying which observations truly constrain the extrinsic parameters and which ones mainly add noise or ambiguity. In this paper, we pr…
Vision based Crop Row Navigation under Varying Field Conditions in Arable Fields
Rajitha de Silva, Grzegorz Cielniak, Junfeng Gao
Accurate crop row detection is often challenged by the varying field conditions present in real-world arable fields. Traditional colour based segmentation is unable to cater for al…
Deep learning-based Crop Row Detection for Infield Navigation of Agri-Robots
Rajitha de Silva, Grzegorz Cielniak, Gang Wang +1
Autonomous navigation in agricultural environments is challenged by varying field conditions that arise in arable fields. State-of-the-art solutions for autonomous navigation in su…
Towards Infield Navigation: leveraging simulated data for crop row detection
Rajitha de Silva, Grzegorz Cielniak, Junfeng Gao
Agricultural datasets for crop row detection are often bound by their limited number of images. This restricts the researchers from developing deep learning based models for precis…
Towards agricultural autonomy: crop row detection under varying field conditions using deep learning
Rajitha de Silva, Grzegorz Cielniak, Junfeng Gao
This paper presents a novel metric to evaluate the robustness of deep learning based semantic segmentation approaches for crop row detection under different field conditions encoun…