Transforming unmanned pineapple picking with spatio-temporal convolutional neural networks

F Meng, J Li, Y Zhang, S Qi, Y Tang - Computers and Electronics in …, 2023 - Elsevier
Automated pineapple harvesting has emerged as a prominent prospective development
within the agricultural domain. Nevertheless, the intricate growth conditions that pineapples …

Remote sensing monitoring of rice diseases and pests from different data sources: A review

Q Zheng, W Huang, Q Xia, Y Dong, H Ye, H Jiang… - Agronomy, 2023 - mdpi.com
Rice is an important food crop in China, and diseases and pests are the main factors
threatening its safety, ecology, and efficient production. The development of remote sensing …

A transfer learning-based artificial intelligence model for leaf disease assessment

V Gautam, NK Trivedi, A Singh, HG Mohamed, ID Noya… - Sustainability, 2022 - mdpi.com
The paddy crop is the most essential and consumable agricultural produce. Leaf disease
impacts the quality and productivity of paddy crops. Therefore, tackling this issue as early as …

[HTML][HTML] Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques

CG Simhadri, HK Kondaveeti, VK Vatsavayi… - Information Processing …, 2024 - Elsevier
Rice is an essential food crop that is cultivated in many countries. Rice leaf diseases can
cause significant damage to crop cultivation, leading to reduced yields and economic …

A mobile-based system for maize plant leaf disease detection and classification using deep learning

F Khan, N Zafar, MN Tahir, M Aqib, H Waheed… - Frontiers in Plant …, 2023 - frontiersin.org
Artificial Intelligence has been used for many applications such as medical, communication,
object detection, and object tracking. Maize crop, which is the major crop in the world, is …

Handling severity levels of multiple co-occurring cotton plant diseases using improved YOLOX model

SK Noon, M Amjad, MA Qureshi, A Mannan - IEEE Access, 2022 - ieeexplore.ieee.org
Automatic detection of plant diseases has emerged as a challenging field in the last decade.
Computer vision-based advancements have helped in the timely and accurate identification …

Research on polygon pest-infected leaf region detection based on YOLOv8

R Zhu, F Hao, D Ma - Agriculture, 2023 - mdpi.com
Object detection in deep learning provides a viable solution for detecting crop-pest-infected
regions. However, existing rectangle-based object detection methods are insufficient to …

Cotton-YOLO: Improved YOLOV7 for rapid detection of foreign fibers in seed cotton

Q Li, W Ma, H Li, X Zhang, R Zhang, W Zhou - Computers and Electronics in …, 2024 - Elsevier
In China, the widespread adoption of machine-picked cotton has greatly improved the
efficiency of cotton harvesting. However, this has significantly increased the presence of …

An enhanced YOLOv5 model for greenhouse cucumber fruit recognition based on color space features

N Wang, T Qian, J Yang, L Li, Y Zhang, X Zheng, Y Xu… - Agriculture, 2022 - mdpi.com
The identification of cucumber fruit is an essential procedure in automated harvesting in
greenhouses. In order to enhance the identification ability of object detection models for …

Derin Evrişimli Sinir Ağları Kullanılarak Pirinç Hastalıklarının Sınıflandırılması

E Vezıroglu, I Pacal, A Coşkunçay - … of the Institute of Science and …, 2023 - dergipark.org.tr
Çeltik, temel bir gıda kaynağıdır ve endüstride sıkça kullanılan nadir bitkilerden biridir. Çeltik
yaprak hastalıklarının erken teşhisi, ekin hasarını en aza indirmek için büyük önem …