Results 121 to 130 of about 12,860 (259)

RF-Based UAV Detection and Identification Using Hierarchical Learning Approach. [PDF]

Sensors (Basel), 2021
Nemer I, Sheltami T, Ahmad I, Yasar AU, Abdeen MAR.   +4 more
europepmc   +1 more source

Deep Reinforcement Learning Based Autonomous Decision‐Making for Cooperative Uncrewed Aerial Vehicles: A Search and Rescue Real World Application

Journal of Field Robotics, EarlyView.
ABSTRACT This paper presents the first end‐to‐end framework that combines guidance, navigation, and centralized task allocation for multiple UAVs performing autonomous search‐and‐rescue (SAR) in GNSS‐denied indoor environments. A twin delayed deep deterministic policy gradient controller is trained with an artificial potential field (APF) reward that ...
Thomas Hickling, Maxwell Hogan, Abdulla Tammam, Nabil Aouf   +3 more
wiley   +1 more source

RF Signal-Based UAV Detection and Mode Classification: A Joint Feature Engineering Generator and Multi-Channel Deep Neural Network Approach. [PDF]

Entropy (Basel), 2021
Yang S, Luo Y, Miao W, Ge C, Sun W, Luo C.   +5 more
europepmc   +1 more source

Validation of a Particle Image Velocimetry Algorithm Through Comparative Field and Laboratory Analysis

River Research and Applications, EarlyView.
ABSTRACT Flow velocity measurement is fundamental to hydrological and hydraulic studies, providing essential data for streamflow estimation and river dynamics analysis. Traditional in situ methods like propeller gauges and acoustic Doppler current profilers are accurate but intrusive and labour‐intensive, while non‐intrusive image processing methods ...
Ghazaleh Nassaji Matin, Gareth Bradbury, Alan Puttock, Kirsty Frith, Diego Panici   +4 more
wiley   +1 more source

Restoring Lateral Connectivity to Anthropogenic Riverscapes: Six Lessons From Stage Zero

River Research and Applications, EarlyView.
ABSTRACT Centuries of river modification, particularly straightening and incision, have severely reduced lateral connectivity between rivers and their floodplains. As a result, Stage 0 riverscapes, characterised by high lateral connectivity (e.g., anastomosing or wetland riverscapes), are now rare in anthropogenic landscapes.
Richard J. Mason, Matthew F. Johnson, Ben Eardley, Matthew J. Hemsworth, Arnaud Foret, Luca Mao, Matt Parr, Alan Puttock, Richard E. Brazier   +8 more
wiley   +1 more source

Riparian Failure: Damming and Flow Stabilization Exclude Cottonwood Colonization Along a Dryland River

River Research and Applications, EarlyView.
ABSTRACT The Marias River flows from Glacier National Park through northcentral Montana, and into the Missouri River. Annual flows gradually declined from 1902 to 2024 (~3.2%/decade) and the 1952 Tiber Dam and Lake Elwell reservoir were operated to attenuate peak flows and stabilize downstream flows year‐round.
Stewart B. Rood, Lori A. Goater
wiley   +1 more source

Insulator fault feature extraction system of substation equipment based on machine vision

IET Networks, EarlyView., 2022
Abstract The artificial intelligence technology and intelligent automation are more and more widely used, the insulators play a supporting and insulating role in the operation of the grid. The use of machine vision inspection technology to detect insulator faults has become an inevitable trend of the times.
Keruo Jiang, Qiaoqun Xia, Lijun Ma, Xin Xu, Zhipeng Shao   +4 more
wiley   +1 more source

Automated object detection based on YOLOv11 for monitoring benthic population dynamics: A new approach combining photogrammetry and open‐source GIS tools applied to sea cucumbers

Remote Sensing in Ecology and Conservation, EarlyView.
This research established a new object detection model based on YOLOv11 to recognise benthic organisms, specifically sea cucumbers, by utilising high‐resolution photogrammetric‐based orthomosaics acquired along infralittoral Mediterranean Sea beds. The model demonstrated impressive performance metrics and, when combined with the Deepness plugin for the
Gian Mario Sangiovanni, Giovanna Jona Lasinio, Daniele Poggio, Gianluca Mastrantonio, Alessio Pollice, Arnold Rakaj, Midhun Mohan, Stefano Moro, Edoardo Casoli, Daniele Ventura   +9 more
wiley   +1 more source

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source

Classification of tree species and standing dead trees in Boreal forests using UAV‐based RGB, multispectral, and LiDAR point clouds

Remote Sensing in Ecology and Conservation, EarlyView.
We evaluated single‐ and multi‐sensor UAV approaches for classifying tree species and standing dead trees in boreal forests, focusing on key biodiversity indicators such as European aspen. Using spectral and structural features extracted from RGB, multispectral (MSP), and LiDAR point clouds for 1,205 field‐measured trees, we compared classification ...
Anton Kuzmin, Lauri Korhonen, Topi Tanhuanpää, Mikko Kukkonen, Matti Maltamo, Timo Kumpula   +5 more
wiley   +1 more source