Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things
In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
A review of computer vision technologies for plant phenoty**
Plant phenotype plays an important role in genetics, botany, and agronomy, while the
currently popular methods for phenotypic trait measurement have some limitations in …
currently popular methods for phenotypic trait measurement have some limitations in …
[HTML][HTML] Convolutional neural networks for image-based high-throughput plant phenoty**: a review
Plant phenoty** has been recognized as a bottleneck for improving the efficiency of
breeding programs, understanding plant-environment interactions, and managing …
breeding programs, understanding plant-environment interactions, and managing …
[HTML][HTML] Leaf only SAM: A segment anything pipeline for zero-shot automated leaf segmentation
Abstract Segment Anything Model (SAM) is a new “foundation model” that can be used as a
zero-shot object segmentation method with the use of either guide prompts such as …
zero-shot object segmentation method with the use of either guide prompts such as …
Real-time plant leaf counting using deep object detection networks
The use of deep neural networks (DNNs) in plant phenoty** has recently received
considerable attention. By using DNNs, valuable insights into plant traits can be readily …
considerable attention. By using DNNs, valuable insights into plant traits can be readily …
Agi for agriculture
G Lu, S Li, G Mai, J Sun, D Zhu, L Chai, H Sun… - ar** by combining domain adaptation with 3D plant model simulations: Application to wheat leaf counting at seedling stage
The number of leaves at a given time is important to characterize plant growth and
development. In this work, we developed a high-throughput method to count the number of …
development. In this work, we developed a high-throughput method to count the number of …
Label-efficient learning in agriculture: A comprehensive review
The past decade has witnessed many great successes of machine learning (ML) and deep
learning (DL) applications in agricultural systems, including weed control, plant disease …
learning (DL) applications in agricultural systems, including weed control, plant disease …
Meta‐learning shows great potential in plant disease recognition under few available samples
X Wu, H Deng, Q Wang, L Lei, Y Gao… - The Plant …, 2023 - Wiley Online Library
Plant diseases worsen the threat of food shortage with the growing global population, and
disease recognition is the basis for the effective prevention and control of plant diseases …
disease recognition is the basis for the effective prevention and control of plant diseases …
Easy domain adaptation method for filling the species gap in deep learning-based fruit detection
W Zhang, K Chen, J Wang, Y Shi… - Horticulture Research, 2021 - academic.oup.com
Fruit detection and counting are essential tasks for horticulture research. With computer
vision technology development, fruit detection techniques based on deep learning have …
vision technology development, fruit detection techniques based on deep learning have …