Aeva Introduces AevaScenes, the First Open-Access FMCW 4D LiDAR and Camera Dataset for Autonomous Vehicle Research

Aeva® (Nasdaq: AEVA), a leader in next-generation sensing and perception systems, today announced the release of AevaScenes, ...

From Geometric Separation to Semantic Understanding: A Deep Analysis of the Essential Differences Between 3D Point Cloud Segmentation and Semantic Segmentation

Among these, 3D point cloud segmentation and semantic segmentation are two key technologies. Although both fall under the category of point cloud processing, there are essential differences in target ...
EurekAlert!

Unsupervised AI network separates wood and leaves in 3D forest scans

A research team has developed a powerful unsupervised deep learning network that can accurately separate wood and leaf components in 3D point clouds of trees—without the need for labor-intensive data ...

Chenyuan Robotics Obtains Patent for Urban Scene Semantic Segmentation, Promoting **Lightweight AI** Implementation

Deeply Engaged in Software and Information Technology Services According to Tianyancha data, Chenyuan Robotics was ...
InfoQ

Unsupervised Object Detection and Semantic Segmentation Using Deep Learning

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
DLR

DLR-SkyScapes: Aerial Semantic Segmentation Dataset for HD-mapping

High-Definition(HD) mapping is in many applications from autonomous driving to infrastructure monitoring, and urban management essential for the understanding of complex urban infrastructure with ...
EurekAlert!

SegVoteNet: A deep learning framework transforms sorghum canopy analysis in the field

A research team introduces a scalable, drone-based 3D reconstruction pipeline combined with a novel deep learning framework—SegVoteNet—to phenotype sorghum panicles in field trials.