Results 191 to 200 of about 2,942 (257)
Advances in Computer Vision and Sensor-Based Methods for Intelligent Power Transmission Line Inspection. [PDF]
Kouris VN, Vrochidou E, Papakostas GA.
europepmc +1 more source
Abstract An agronomic trait such as stand count is important for cultivar development and crop management practices. Manually counting the number of plants is time consuming, labor‐intensive, and prone to error. The use of unoccupied aerial systems (UAS)‐collected red, green, blue (RGB) imagery in conjunction with advanced deep learning and image ...
Aliasghar Bazrafkan +1 more
wiley +1 more source
Sensors in Self-Driving Vehicles: A Detailed Literature Review and New Trends. [PDF]
Viktor P, Kiss G.
europepmc +1 more source
Abstract Multispectral three‐dimensional (3D) imaging offers substantial potential for plant phenotyping, yet manual segmentation of plant organs remains a bottleneck in breeding programs. We developed a color‐based filtering workflow for faba bean (Vicia faba L.) point clouds that optimizes lower and upper thresholds of spectral indices and broadband ...
Lennart Scheer +6 more
wiley +1 more source
Cross-modal data integration and spectral optimization for enhanced individual apple tree canopy nitrogen concentration estimation using UAV remote sensing. [PDF]
Chen B, Zhang N, Li Y, Li Z, Chai X.
europepmc +1 more source
Genomic and phenomic prediction models improve selection accuracy for complex traits in alfalfa
Abstract Predictive breeding has been proposed as an effective approach to accelerate genetic gain for complex traits. Genomic prediction (GP) models have been developed in alfalfa (Medicago sativa L.) for key traits in the last decade. More recently, phenomic prediction (PP) models have been proposed as a low‐cost, high‐throughput alternative to GP in
Pablo Sipowicz +8 more
wiley +1 more source
Close-Range 3D Hyperspectral Measurement System with a Physics-Guided Spectral Correction Model. [PDF]
Liu Z +8 more
europepmc +1 more source
Dual‐Branch Network With Enhanced Feature Fusion for Improved Rice Classification Accuracy
ABSTRACT Accurate mapping of rice, one of the world's most important food crops, is critical for monitoring its growth, estimating yields, and supporting global food security. Most deep learning methods for crop classification rely on multi‐temporal optical remote sensing data. However, it is difficult to obtain sufficient ground‐truth samples for time‐
Rongfei Ma +6 more
wiley +1 more source
IR-Action Spectroscopy of the Astrochemically Relevant HCCS<sup>+</sup> Cation. [PDF]
Michielan M +9 more
europepmc +1 more source
Overview of AI‐powered surveillance technologies, applications, challenges, limitations, and deployment considerations. ABSTRACT Artificial intelligence (AI) has rapidly transformed smart surveillance systems, significantly leveraging technologies such as deep learning, computer vision, and adaptive monitoring.
Tanzila Kehkashan +7 more
wiley +1 more source

