Results 171 to 180 of about 268,742 (315)

Evaluating machine learning models for multi‐species wildlife detection and identification on remote sensed nadir imagery in South African savanna

Wildlife Biology, EarlyView.
This research paper investigates the efficacy of leading machine learning (ML) models for detecting and identifying ungulate species in African savanna using nadir imagery from unmanned aerial vehicles (UAVs). Traditional aerial counting methods, while widely used, suffer from significant limitations in accuracy and precision, in part due to human ...
Paul Allin, Fadel Seydou, Radloff Frans, Andrew Davies, Alison Leslie   +4 more
wiley   +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

Dynamic Resource Allocation Optimisation and Security‐Resilient Control for Bandwidth‐Limited Network Control Systems With Data Conflicts

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Networked control systems (NCSs) often suffer from performance degradation due to limited communication bandwidth, which can cause data transmission conflicts and packet loss. Existing scheduling strategies may fail to simultaneously meet the real‐time requirements and the importance of multisensor data, and they are particularly vulnerable ...
Da Chen, Kaibo Shi, Bin Guo, Kangkang Sun, Huaicheng Yan, Xiao Cai   +5 more
wiley   +1 more source

Unmanned Aerial Vehicle

International Journal for Research in Applied Science and Engineering Technology, 2021
openaire   +1 more source

A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia, Zhan Lin, Xingyan Wang, Ruixi Huang, Jinhui Hu, Yang Hu, Huaqing Li   +6 more
wiley   +1 more source

New frontiers for unmanned aerial vehicles in planetary health research. [PDF]

BMC Glob Public Health
Bramante JT, Tarpenning MS, Woo KE, Chamberlin AJ, Coombe KD, Rosser JI.   +5 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

Particle Filtering-Based In-Flight Icing Detection for Unmanned Aerial Vehicles. [PDF]

Sensors (Basel)
Souanef T, Tadjine M, Horri N, Chaabeni I, Boulassel B.   +4 more
europepmc   +1 more source

LINA's testing infrastructure enables AI to take-off in unmanned aerial vehicles (UAVs). [PDF]

Front Robot AI
Bolck HA, Vollenweider J, Merkli F, Barden A, Jajcay M, Trempeck P, Rafailović B, Fraefel R, Lenhart PM, Chavarriaga R, Renold M, Bogojeska J, Stadelmann T, Guillaume M.   +13 more
europepmc   +1 more source

Climatic–Anthropogenic Synergy Drives Escalating Minimum Area Requirements and Connectivity‐Protection Mismatch in a Karst‐Endemic Primate

Integrative Zoology, EarlyView.
Climate change and anthropogenic activities drive antagonistic degradation of landscape connectivity for endangered François’ langur (1987–2024), causing 48.8% habitat loss, north‐south fragmentation, and centroid migration (1.2 km/yr). Despite protected areas buffering connectivity, static management fails dynamic priority habitats; we propose ...
Guangmei Yang, Heqin Cao, Tuo Shen, Jipeng Tian, Yixin Diao, Haijun Su   +5 more
wiley   +1 more source