PlantBiCNet: A new paradigm in plant science with bi-directional cascade neural network for detection and counting

J Ye, Z Yu, Y Wang, D Lu, H Zhou - Engineering Applications of Artificial …, 2024 - Elsevier
Deep learning is increasingly popular for precise plant detection and counting in computer
vision applications. Despite the rising cross-disciplinary research in this field, an important …
R Chen, H Lu, Y Wang, Q Tian, C Zhou… - Frontiers in Plant …, 2024 - frontiersin.org
Introduction Rice (Oryza sativa) serves as a vital staple crop that feeds over half the world's
population. Optimizing rice breeding for increasing grain yield is critical for global food …

GSP-AI: An AI-Powered Platform for Identifying Key Growth Stages and the Vegetative-to-Reproductive Transition in Wheat Using Trilateral Drone Imagery and …

L Shen, G Ding, R Jackson, M Ali, S Liu, A Mitchell… - Plant …, 2024 - spj.science.org
Wheat (Triticum aestivum) is one of the most important staple crops worldwide. To ensure its
global supply, the timing and duration of its growth cycle needs to be closely monitored in …

Vision foundation model for agricultural applications with efficient layer aggregation network

J Ye, Z Yu, J Lin, H Li, L Lin - Expert Systems with Applications, 2024 - Elsevier
Agricultural production is transitioning from traditional tools to IoT-connected automation
devices. The integration of computer vision and agricultural automation is becoming closer …

Feature diffusion reconstruction mechanism network for crop spike head detection

R Ming, Q Gong, C Yang, H Luo, C Song… - Frontiers in Plant …, 2024 - frontiersin.org
Introduction Monitoring crop spike growth using low-altitude remote sensing images is
essential for precision agriculture, as it enables accurate crop health assessment and yield …

Rice-yolo: In-field rice spike detection based on improved yolov5 and drone images

M Lan, C Liu, H Zheng, Y Wang, W Cai, Y Peng, C Xu… - Agronomy, 2024 - mdpi.com
The rice spike, a crucial part of rice plants, plays a vital role in yield estimation, pest
detection, and growth stage management in rice cultivation. When using drones to capture …

Breeding 4.0 vis-à-vis application of artificial intelligence (AI) in crop improvement: an overview

R Ansari, A Manna, S Hazra, S Bose… - New Zealand Journal …, 2024 - Taylor & Francis
The field of plant breeding has witnessed significant transformations over millennia evolving
from rudimentary selection strategies (Breeding 1.0) in ancient times to sophisticated …

Phenoty** of Panicle Number and Shape in Rice Breeding Materials Based on Unmanned Aerial Vehicle Imagery

X Lu, Y Shen, J **e, X Yang, Q Shu, S Chen… - Plant …, 2024 - spj.science.org
The number of panicles per unit area (PNpA) is one of the key factors contributing to the
grain yield of rice crops. Accurate PNpA quantification is vital for breeding high-yield rice …