SSM-Net for Plants Disease Identification in Low Data Regime
Plant disease detection is an essential factor in increasing agricultural production. Due to the difficulty of disease detection, farmers spray various pesticides on their crops to protect them, causing great harm to crop growth and food standards. Deep learning can offer critical aid in detecting such diseases. However, it is highly inconvenient to collect a large volume of data on all forms of the diseases afflicting a specific plant species. In this paper, we propose a new metrics-based few-shot learning SSM net architecture, which consists of stacked siamese and matching network components to address the problem of disease detection in low data regimes. We demonstrated our experiments on two datasets: mini-leaves diseases and sugarcane diseases dataset. We have showcased that the SSM-Net approach can achieve better decision boundaries with an accuracy of 92.7% on the mini-leaves dataset and 94.3% on the sugarcane dataset. The accuracy increased by ~10% and ~5% respectively, compared to the widely used VGG16 transfer learning approach. Furthermore, we attained F1 score of 0.90 using SSM Net on the sugarcane dataset and 0.91 on the mini-leaves dataset. Our code implementation is available on Github: https://github.com/shruti-jadon/PlantsDiseaseDetection.
Code (1)
Tasks
Few-Shot LearningTransfer LearningMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Deep learning models for plant disease detection and diagnosis
In this paper, convolutional neural network models were developed to perform plant disease detection and diagnosis using simple leaves images of healthy and diseased plants, through deep learning methodologies. Trainin…
Deep LearningTransfer Learning With Densenet201 Architecture Model For Potato Leaf Disease Classification
Potato plants are plants that are beneficial to humans. Like other plants in general, potato plants also have diseases; if this disease is not treated immediately, there will be a significant decrease in food production.…
ClassificationTransfer LearningA Multi-Plant Disease Diagnosis Method using Convolutional Neural Network
A disease that limits a plant from its maximal capacity is defined as plant disease. From the perspective of agriculture, diagnosing plant disease is crucial, as diseases often limit plants' production capacity. However,…
ClassificationGeneral ClassificationMulti-class ClassificationPlantSeg: A Large-Scale In-the-wild Dataset for Plant Disease Segmentation
Plant diseases pose significant threats to agriculture. It necessitates proper diagnosis and effective treatment to safeguard crop yields. To automate the diagnosis process, image segmentation is usually adopted for prec…
Benchmarkingimage-classificationImage ClassificationImage Segmentation+2Optical Screening of Citrus Leaf Diseases Using Label-Free Spectroscopic Tools: A Review
Citrus diseases pose threats to citrus farming and result in economic losses worldwide. Nucleic acid and serology-based methods of detection and, immunochromatographic assays are commonly used but these laboratory tests …