[HTML][HTML] Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
[HTML][HTML] Review on convolutional neural network (CNN) applied to plant leaf disease classification
J Lu, L Tan, H Jiang - Agriculture, 2021 - mdpi.com
Crop production can be greatly reduced due to various diseases, which seriously endangers
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …
Classification and detection of insects from field images using deep learning for smart pest management: A systematic review
W Li, T Zheng, Z Yang, M Li, C Sun, X Yang - Ecological Informatics, 2021 - Elsevier
Insect pest is one of the main causes affecting agricultural crop yield and quality all over the
world. Rapid and reliable insect pest monitoring plays a crucial role in population prediction …
world. Rapid and reliable insect pest monitoring plays a crucial role in population prediction …
[HTML][HTML] Pre-trained deep neural network-based features selection supported machine learning for rice leaf disease classification
Rice is a staple food for roughly half of the world's population. Some farmers prefer rice
cultivation to other crops because rice can thrive in a wide range of environments. Several …
cultivation to other crops because rice can thrive in a wide range of environments. Several …
[HTML][HTML] A systematic review on automatic insect detection using deep learning
Globally, insect pests are the primary reason for reduced crop yield and quality. Although
pesticides are commonly used to control and eliminate these pests, they can have adverse …
pesticides are commonly used to control and eliminate these pests, they can have adverse …
[HTML][HTML] YOLO-based detection of Halyomorpha halys in orchards using RGB cameras and drones
This paper explores the utilization of innovative technologies such as RGB cameras, drones,
and computer vision algorithms, for monitoring pests in orchards, with a specific focus on …
and computer vision algorithms, for monitoring pests in orchards, with a specific focus on …
我国智能农机的研究进展与无人农场的实践
罗锡文, 廖娟, 胡炼, 周志艳, 张智刚, 臧英… - 华南农业大学 …, 2021 - journal.scau.edu.cn
智慧农业是现代农业的高级形式, 无人农场是实现智慧农业的重要途径, 智能农机是无人农场的
物质支撑. 本文以植物生产为例, 介绍了智能农机的智能感知, 自动导航, 精准作业和智慧管理4 …
物质支撑. 本文以植物生产为例, 介绍了智能农机的智能感知, 自动导航, 精准作业和智慧管理4 …
[HTML][HTML] Metal surface defect detection using modified YOLO
Y Xu, K Zhang, L Wang - Algorithms, 2021 - mdpi.com
Aiming at the problems of inefficient detection caused by traditional manual inspection and
unclear features in metal surface defect detection, an improved metal surface defect …
unclear features in metal surface defect detection, an improved metal surface defect …
Recognition and counting of typical apple pests based on deep learning
T Wang, L Zhao, B Li, X Liu, W Xu, J Li - Ecological Informatics, 2022 - Elsevier
The recognition and counting of apple pests sampled by different sex attractants are very
important and significant for pest control. Convolutional neural networks (CNNs) are …
important and significant for pest control. Convolutional neural networks (CNNs) are …
农业害虫检测的深度学习算法综述.
蒋心璐, 陈天恩, 王聪, 李书琴… - Journal of Computer …, 2023 - search.ebscohost.com
害虫检测是害虫测报的关键步骤, 对于害虫防治具有重要意义, 也是保证农作物产量和品质的
前提. 近年来, 随着卷积神经网络的迅速发展, 害虫检测技术进入智能化时代 …
前提. 近年来, 随着卷积神经网络的迅速发展, 害虫检测技术进入智能化时代 …