International Journal for Numerical Methods in Biomedical Engineering 37 (6 … The International Archives of the Photogrammetry, Remote Sensing and Spatial …

Reliable and automated 3-dimensional (3D) plant shoot segmentation is a core prerequisite for the extraction of plant phenotypic traits at the organ level. Combining deep learning and point clouds...

Liyi Luo PhD student, Bioresource Engineering, McGill University. Joined ; November 2023

2022年12月20日 · In our work, we proposed a novel weakly supervised framework, Eff-3DPSeg, for 3D plant shoot segmentation. First, high-resolution point clouds of soybean were reconstructed using a low-cost photogrammetry system, and the Meshlab-based Plant Annotator was developed for plant point cloud annotation.

Liyi Luo, Xintong Jiang, Yu Yang, Eugene Roy Antony Samy, Mark Lefsrud, Valerio Hoyos-Villegas, Shangpeng Sun: Eff-3DPSeg: 3D organ-level plant shoot segmentation using annotation-efficient point clouds. CoRR abs/2212.10263 (2022)

2023年7月27日 · Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely recognized that realistic sensor simulation will play a critical role in solving remaining corner cases by simulating them. To this end, we propose an autonomous driving simulator based upon neural radiance fields (NeRFs).

Physics-based simulation is crucial for robotic arm control and reinforcement learning, yet bridging the Real2Sim and Sim2Real gaps remains challenging due to the complex properties of robots and manipulated objects.

ORCID record for Liyi Luo. ORCID provides an identifier for individuals to use with their name as they engage in research, scholarship, and innovation activities.

Affiliations: [Institute for AI Industry Research (AIR), Tsinghua University, China, McGill University, Canada].

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