A Detection Method of Pine Wilt Disease Based on Improved YOLOv11 With UAV Remote Sensing Images. [PDF]
Shi H +6 more
europepmc +1 more source
Transmission Line Vibration Damper Detection Using Deep Neural Networks Based on UAV Remote Sensing Image. [PDF]
Chen W, Li Y, Zhao Z.
europepmc +1 more source
ABSTRACT This study analyzes the architecture of the beyond 5G‐NTN (Non‐terrestrial Network) integrated network and presents the technical, legal, and regulatory challenges and considerations for expanding the Artificial Intelligence of Things (AIoT) ecosystem.
Byung Woon Kim, Ga Eun Choi
wiley +1 more source
Application of UAV remote sensing for vegetation identification: a review and meta-analysis. [PDF]
Chang B +5 more
europepmc +1 more source
Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing. [PDF]
de Oliveira GS +15 more
europepmc +1 more source
Formal Approach to Safety‐Driven Dynamic Procedure Modeling
ABSTRACT Ensuring the safety of unmanned aerial systems (UAS) is a growing concern as the number of UAS grows increasingly fast. Regulatory bodies are in the process of tackling this problem by issuing standards and recommendations to be met by UAS designers.
Jean‐Charles Chaudemar +3 more
wiley +1 more source
RSW-YOLO: A Vehicle Detection Model for Urban UAV Remote Sensing Images. [PDF]
Wang H +6 more
europepmc +1 more source
Weed Density Extraction Based on Few-Shot Learning Through UAV Remote Sensing RGB and Multispectral Images in Ecological Irrigation Area. [PDF]
Wang S +6 more
europepmc +1 more source
Uncertainties exist in the biosphere–climate feedbacks in the Arctic. Remote and ground measurements play complementary roles in detecting possible changes. A critical next step is identification of key drivers of the global changes for future projections. ABSTRACT Positive biosphere–climate feedbacks are likely to amplify the Arctic warming, yet major
Akira S. Mori +10 more
wiley +1 more source
Retraction Note: Forest pest monitoring and early warning using UAV remote sensing and computer vision techniques. [PDF]
Li X, Wang A.
europepmc +1 more source

