Results 231 to 240 of about 148,136 (310)

Quantifying microhabitat selection of snowshoe hares using forest metrics from UAS‐based LiDAR

Wildlife Biology, EarlyView.
Identifying the spatial and temporal scale at which animals select resources is critical for predicting how populations respond to changes in the environment. The spatial distribution of fine‐scale resources (e.g. patches of dense vegetation) are often linked with critical life‐history requirements such as denning and feeding sites.
Alexej P. K. Sirén, Franklin Sullivan, Rachel Cliché, Jeremy Goetz, Leighlan S. Prout, Jillian Kilborn, Katelyn Courtot, Michael Palace   +7 more
wiley   +1 more source

Online Extrinsic Calibration of Camera and LiDAR Based on Cascade Optimization. [PDF]

Sensors (Basel)
Hou C, He Z, Zhao T, Guo Z, Ji X.
europepmc   +1 more source

Estimating red deer Cervus elaphus population density using drones in a steep and rugged terrain

Wildlife Biology, EarlyView.
Precise and accurate information about population density, crucial for wildlife management, is difficult to obtain for elusive species living in dense forests or steep and inaccessible terrain. Using unmanned aerial vehicles (UAVs), we developed a method for obtaining absolute population estimates of ungulates living in steep, rugged, and partly ...
Julie Bommerlund, Torbjørn Ergon, Simon Filhol, Atle Mysterud   +3 more
wiley   +1 more source

An Energy-Efficient LiDAR Receiver Using Time-to-Voltage Converter and SAR ADC in 180 nm CMOS. [PDF]

Micromachines (Basel)
Seo B, Park SM.
europepmc   +1 more source

Target-less registration of UAV-LiDAR point clouds based on graph matching of tree locations in forest environments. [PDF]

Sci Rep
Fekry R, Ali E, Sani-Mohammed A, Abdallah M, Amr D.   +4 more
europepmc   +1 more source

CDFNet: Cross‐Modal Deep Fusion for Monocular 3D Semantic Scene Completion

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Semantic scene completion (SSC) aims to predict the semantic occupancy and geometry of 3D scenes. Recently, most studies focus on camera‐based approaches due to the rich visual cues of images and the cost‐effectiveness of cameras. However, these methods usually lack efficient fusion and fine‐grained processing of cross‐modal semantic ...
Xianjing Cheng, Lintai Wu, Jie Wen, Tianhao Peng, Yong Xu, Zairong Wei   +5 more
wiley   +1 more source

PickAMoo: LIDAR-enhanced mask R-CNN segmentation for precision weight estimation in dairy cattle using smartphone imaging. [PDF]

Sci Rep
Guzhva O, Ternman E, Lindberg M, Telezhenko E, Kronqvist C.   +4 more
europepmc   +1 more source

A Robust Visual Inertial Odometry SLAM Considering Robot Self Dynamics

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT In this paper, to deal with the dynamic SLAM problem, we investigate feature tracking and IMU preintegration in visual‐inertial odometry (VIO) and design a robust SLAM framework that explicitly considers robot self‐dynamics. We propose a self‐dynamics and IMU‐aided feature tracker to predict initial optical flow and an iterative refinement ...
Junyin Qiu, Hong Liu, Tianwei Zhang
wiley   +1 more source

SGMR-LPR: A Semantic-Guided Network Robust to Movable Objects for LiDAR-Based Place Recognition. [PDF]

Sensors (Basel)
Jiang W, Xiao Z, Qian L, Shang E, Zhao D, Zhu Q, Xiao L.   +6 more
europepmc   +1 more source

Modelling the Four‐Dimensional Power Line Sag Dynamics by Point Signature in Time‐Series Synthetic‐Aperture Radar Images

High Voltage, EarlyView.
ABSTRACT Power lines in synthetic‐aperture radar (SAR) images are reflected as point signatures, which fluctuate annually in both the azimuth and range directions. A novel framework is proposed in this paper to evaluate the four‐dimensional dynamic status of power line sag using those point signatures in time‐series SAR images.
Sijie Ma, Tao Li, Mahdi Motagh, Yan Liu, Yangmao Wen   +4 more
wiley   +1 more source