Detection of potato diseases using image segmentation and multiclass support vector machine
Explore this paper's citation graph
- Type
- article
- Published
- 2017-04-01
- Cited by
- 428
- References
- 12
- Access
- Open access
- OpenAlex
- https://openalex.org/W2714342494
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:6339549
Keywords
Support vector machine, Artificial intelligence, Image segmentation, Computer science, Pattern recognition (psychology)
References
- Use of leaf color images to identify nitrogen and potassium deficient tomatoes
- Application of neural networks to image recognition of plant diseases
- Early diagnostics of macronutrient deficiencies in three legume species by color image analysis
- Digital Image Sensor-Based Assessment of the Status of Oat (Avena sativa L.) Crops after Frost Damage
- Applications of Image Processing in Agriculture: A Survey
- Investigation on Image Processing Techniques for Diagnosing Paddy Diseases
- Application of Support Vector Machine for Detecting Rice Diseases Using Shape and Color Texture Features
- Rice disease identification using pattern recognition techniques
- Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants
- [Detection of Late Blight Disease on Potato Leaves Using Hyperspectral Imaging Technique].
- Using Deep Learning for Image-Based Plant Disease Detection
- Paddy diseases identification with texture analysis using fractal descriptors based on fourier spectrum
Cited by
- A Deep Learning Enabled Multi-Class Plant Disease Detection Model Based on Computer Vision
- Identification of Apple Leaf Diseases Based on Deep Convolutional Neural Networks
- A review on: Various techniques of plant leaf disease detection
- A novel approach to classify and detect bean diseases based on image processing
- CCDF: Automatic system for segmentation and recognition of fruit crops diseases based on correlation coefficient and deep CNN features
- Comparision of Performance of Classifiers - SVM, RF and ANN in Potato Blight Disease Detection Using Leaf Images
- Current and future applications of statistical machine learning algorithms for agricultural machine vision systems
- Applications of Computer Vision in Plant Pathology: A Survey
- Automatic Recognition of Guava Leaf Diseases using Deep Convolution Neural Network
- Leaf Disease Detection and Recommendation of Pesticides Using Convolution Neural Network
- Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolutional Neural Networks
- A Review on Machine Learning Classification Techniques for Plant Disease Detection
- Study on Machine Learning for Identification of Farmer’s Query in Kannada Language
- Weakly-supervised learning approach for potato defects segmentation
- DEVELOPMENT OF A MACHINE VISION SYSTEM FOR STRAWBERRY POWDERY MILDEW DISEASE DETECTION
- Potato defects classification and localization with convolutional neural networks
- A Novel Method for Plant Leaf Malady Recognition using Machine Learning Classifiers
- An Efficient Deep Learning Model for Olive Diseases Detection
- Disease Detection in Plant using Artificial Neural Network
- Development of Tomato Septoria Leaf Spot and Tomato Mosaic Diseases Detection Device Using Raspberry Pi and Deep Convolutional Neural Networks
Related papers
- Segmentation of 3D medical image data sets with a combination of region-based initial segmentation and active surfaces
- A real-time parallel combination segmentation method for aluminum surface defect images
- Application of a new improved image segmentation algorithm in car plate recognition
- Medical Image Segmentation
- A Panoramic Segmentation Network for Point Cloud
- PROPAGATING DISTRIBUTIONS FOR SEGMENTATION OF BRAIN ATLAS
- Image Segmentation Technology Based on Genetic Algorithm
- An Improved PDE-based GAC Level Set Image Segmentation Algorithm
- Threshold-based Segmentation for 3D Medical Volumetric Images