Advancing precision agriculture: The potential of deep learning for cereal plant head detection

A Sanaeifar, ML Guindo, A Bakhshipour… - … and Electronics in …, 2023 - Elsevier
Cereal plant heads must be identified precisely and effectively in a range of agricultural
applications, including yield estimation, disease detection, and breeding. Traditional …

A survey of deep learning-based object detection methods in crop counting

Y Huang, Y Qian, H Wei, Y Lu, B Ling, Y Qin - Computers and Electronics in …, 2023 - Elsevier
Crop counting is a crucial step in crop yield estimation. By counting, crop growth status can
be accurately detected and adjusted, improving crop yield and quality. In recent years, with …

Detection method of wheat spike improved YOLOv5s based on the attention mechanism

H Zang, Y Wang, L Ru, M Zhou, D Chen… - Frontiers in Plant …, 2022 - frontiersin.org
In wheat breeding, spike number is a key indicator for evaluating wheat yield, and the timely
and accurate acquisition of wheat spike number is of great practical significance for yield …

Detection and counting of maize leaves based on two-stage deep learning with UAV-based RGB image

X Xu, L Wang, M Shu, X Liang, AZ Ghafoor, Y Liu… - Remote Sensing, 2022 - mdpi.com
Leaf age is an important trait in the process of maize (Zea mays L.) growth. It is significant to
estimate the seed activity and yield of maize by counting leaves. Detection and counting of …

A detection approach for late-autumn shoots of litchi based on unmanned aerial vehicle (UAV) remote sensing

J Liang, X Chen, C Liang, T Long, X Tang, Z Shi… - … and Electronics in …, 2023 - Elsevier
Litchi is one of the most common economic fruits in southern China, however, the growth of
late-autumn shoots of litchi hinders flower bud differentiation and reduces yield of fruit. The …

YOLOv7-MA: Improved YOLOv7-based wheat head detection and counting

X Meng, C Li, J Li, X Li, F Guo, Z Xiao - Remote Sensing, 2023 - mdpi.com
Detection and counting of wheat heads are crucial for wheat yield estimation. To address the
issues of overlapping and small volumes of wheat heads on complex backgrounds, this …

Detecting wheat heads from UAV low-altitude remote sensing images using Deep Learning based on transformer

J Zhu, G Yang, X Feng, X Li, H Fang, J Zhang, X Bai… - Remote Sensing, 2022 - mdpi.com
The object detection method based on deep learning convolutional neural network (CNN)
significantly improves the detection performance of wheat head on wheat images obtained …

Improved YOLO-FastestV2 wheat spike detection model based on a multi-stage attention mechanism with a LightFPN detection head

S Qing, Z Qiu, W Wang, F Wang, X Jin, J Ji… - Frontiers in Plant …, 2024 - frontiersin.org
The number of wheat spikes has an important influence on wheat yield, and the rapid and
accurate detection of wheat spike numbers is of great significance for wheat yield estimation …

AutoOLA: Automatic object level augmentation for wheat spikes counting

A Zaji, Z Liu, G Xiao, P Bhowmik, JS Sangha… - … and Electronics in …, 2023 - Elsevier
The ability to count wheat spikes is one of the most critical indicators in wheat plant
agriculture that correlates positively with yield estimation. Numerous studies have …

MFNet: Multi-scale feature enhancement networks for wheat head detection and counting in complex scene

Y Qian, Y Qin, H Wei, Y Lu, Y Huang, P Liu… - … and Electronics in …, 2024 - Elsevier
Developing a high-precision wheat head detection algorithm is challenging due to the
dense distribution and diverse sizes of wheat head in the field, as well as serious coverage …