Sen Yang's research while affiliated with Gansu Agricultural University and other places
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Publications (8)
Introduction
Accurate detection of potato seedlings is crucial for obtaining information on potato seedlings and ultimately increasing potato yield. This study aims to enhance the detection of potato seedlings in drone-captured images through a novel lightweight model.
Methods
We established a dataset of drone-captured images of potato seedlings a...
Diseases cause crop yield reduction and quality decline, which has a great impact on agricultural production. Plant disease recognition based on computer vision can help farmers quickly and accurately recognize diseases. However, the occurrence of diseases is random and the collection cost is very high. In many cases, the number of disease samples...
Potato diseases and pests have a serious impact on the quality and yield of potatoes, and timely prevention and control of potato diseases and pests is essential. A rich knowledge reserve of potato diseases and pests is one of the most important prevention and control measures; however, valuable knowledge is buried in the massive data of potato dis...
The high performance of deep learning networks relies mainly on massive data. However, collecting enough samples of crop disease is impractical, which significantly limits the intelligent diagnosis of diseases. In this study, we propose Heterogeneous Metric Fusion Network-based Few-Shot Learning (HMFN-FSL), which aims to recognize crop diseases wit...
Potato malformation seriously affects commercial value, and its removal has become one of the core steps in the post-harvest and pre-sales process of potatoes. At present, this work mainly relies on manual visual inspection, which requires a lot of labor and incurs high investment costs. Therefore, precise and efficient automatic detection technolo...
Potato canopy nitrogen content (CNC) is an imperative metric for assessing potato growth status and guiding field management. While the spectral index can be utilized to estimate CNC, its efficacy is influenced by the environment and crop type. To address this issue, we utilized hyperspectral indices (HIs) optimization for CNC estimation. Using the...
Above-ground biomass (AGB) is one of the most important indicators for evaluating potato growth and yield. Rapid and accurate biomass estimation is of great significance to potato breeding and agricultural production. However, high cost, large data volume, and poor model scalability are the main problems of hyperspectral remote sensing and LiDAR in...
Citations
... Some tubers, like potatoes, growing underground, prevent direct characterization of productive organs. As a result, estimating plant geometry and above-ground biomass is of great interest for the agronomic insights it can provide [89][90][91]. ...
... CoatNet - [40] To improve real-time detection precision, strengthen essential features, and weaken unrelated features, this study introduced squeeze-andexcitation networks, efficient channel attention (ECA), and convolutional block attention modules into Faster Region-based Convolutional Neural Networks (R-CNN), YOLOx, and single shot multi-box detectors (SSD). ...
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