Results 101 to 110 of about 17,303 (233)

Semi‐automated seal detection on the Western Antarctic Peninsula: an unsupervised machine learning approach for detecting ice seals in aerial survey data

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a semi‐automated, rule‐based image analysis pipeline to detect ice seals in aerial surveys of the Western Antarctic Peninsula during an unusually low sea ice year. By using simple hierarchical clustering instead of deep learning, the method substantially reduced human annotation effort while achieving 82% recall, identifying 758 ...
Claire McGinnity, Connor C.G. Bamford, Nathan Fenney, Andrew Fleming, Jaume Forcada, Michael S. Tift, Luis A. Hückstädt, Daniel P. Costa, Peter T. Fretwell   +8 more
wiley   +1 more source

The Application of Inertial Measurement Unit in Inertia Parameter Identification [PDF]

, 2011
This paper presents a simple but effective method for inertial parameter identification with symmetrical trifilar pendulum and inertial measurement unit (IMU).
Shang Qiu Shan, Bo Wang, Xian Zhong Gao, Zhong Xi Hou   +3 more
core   +1 more source

A Comparison of Mobile Laser Scanning Data Acquisition Methods in Closed Forest, Open Woodland and Sub‐Alpine Woodland Ecosystems

Remote Sensing in Ecology and Conservation, EarlyView.
This study demonstrates that the mobile laser scanning (MLS) sampling density required to reliably characterise vegetation structure increases with a site's structural complexity. Applying a five‐level acquisition framework across open woodland, closed forest and sub‐alpine woodland ecosystems, we found that longer scanning paths increased the ...
Johann Tiede, Karin Reinke, Trung H. Nguyen, Simon Jones   +3 more
wiley   +1 more source

Study of inertial measurement unit sensor [PDF]

, 2009
Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.This paper contains the study about the inertial measurement unit (IMU ...
Mohd Sofian, Mohammad Rosbi, Hazry, Desa, Zul Azfar, Ahmam   +2 more
core  

T‐800: An 800 Hz Data Glove for Precise Hand Gesture Tracking

SmartBot, EarlyView.
Hand motion capture provides critical insights into human dexterity and facilitates advancements in robotic manipulation, yet existing systems are limited by a trade‐off between temporal resolution and visual occlusion. Here, the authors present T‐800, a high‐bandwidth data glove achieving synchronized full‐hand motion capturing at 800 Hz.
Haoyang Luo, Zihang Zhao, Leiyao Cui, Saiyao Zhang, Liu Yang, Zhi Han, Xiyuan Tang, Yixin Zhu   +7 more
wiley   +1 more source

IMPLEMENTASI FILTER KALMAN PADA SISTEM SENSOR INERTIAL MEASUREMENT UNIT (IMU) QUADCOPTER [PDF]

, 2016
Sensor MPU 6050 merupakan salah satu sensor yang tergolong dalam Inertial Measurement Unit (IMU), sensor ini merupakan gabungan dari 3-axis gyroscope dan 3-axis accelerometer. Pada penggunaannya, sensor ini dapat memberikan keluaran sudut kemiringan pada
Rippun, Ferry, Jonathan, Nico
core   +2 more sources

Damping Rotating Grid SINS Based on a Kalman Filter for Shipborne Application

IEEE Access, 2019
The measurement error of the inertial measurement unit (IMU) significantly affects the navigation accuracy of the grid strap-down inertial navigation system (SINS) applied in polar regions.
Tao Fang, Weiquan Huang, Li Luo
doaj   +1 more source

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

Optimal deep learning activity recognition pipeline using animal bio‐logging data

Methods in Ecology and Evolution, EarlyView.
Abstract Animal activity recognition using supervised machine learning on bio‐logging data has revolutionized behavioural studies on wildlife and livestock over the past decade. These studies' analytic pipelines differ substantially though, being based on various sensors, features, algorithms and hyperparameter values, which has caused suboptimal or ...
Jasper A. J. Eikelboom
wiley   +1 more source

Error Compensation Method for Pedestrian Navigation System Based on Low-Cost Inertial Sensor Array

Sensors
In the pedestrian navigation system, researchers have reduced measurement errors and improved system navigation performance by fusing measurements from multiple low-cost inertial measurement unit (IMU) arrays.
Lijia Cao, Xiao Luo, Lei Liu, Guoqing Wang, Jie Zhou   +4 more
doaj   +1 more source