Nothing Special   »   [go: up one dir, main page]

Meena et al., 2022 - Google Patents

Plant Diseases Detection Using Deep Learning

Meena et al., 2022

Document ID
5460701224056506139
Author
Meena M
Monisha G
et al.
Publication year
Publication venue
2022 1st International Conference on Computational Science and Technology (ICCST)

External Links

Snippet

Food is a very important part of our life, it is the most basic need of every living creature on earth our planet, Agriculture is especially crucial as it's our main staple. As the population grows agriculture strives to achieve food products for the growing population and also plant …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6228—Selecting the most significant subset of features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6256—Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6279—Classification techniques relating to the number of classes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G06K9/00147—Matching; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details

Similar Documents

Publication Publication Date Title
Panchal et al. Plant diseases detection and classification using machine learning models
Kulkarni et al. Rice leaf diseases detection using machine learning
Nigam et al. Paddy leaf diseases recognition and classification using PCA and BFO-DNN algorithm by image processing
Gining et al. Harumanis mango leaf disease recognition system using image processing technique
Mohammadpoor et al. An intelligent technique for grape fanleaf virus detection
Bondre et al. Review on leaf diseases detection using deep learning
Borman et al. Classification of Medicinal Wild Plants Using Radial Basis Function Neural Network with Least Mean Square
Sunitha et al. Modeling convolutional neural network for detection of plant leaf spot diseases
Al-Shalout et al. Detecting date palm diseases using convolutional neural networks
Benlachmi et al. Fruits disease classification using machine learning techniques
Diker et al. An effective feature extraction method for olive peacock eye leaf disease classification
Ahmed et al. An approach to identify and classify agricultural crop diseases using machine learning and deep learning techniques
Raja et al. Convolutional neural networks based classification and detection of plant disease
Banerjee et al. Mango Disease Detection System Using CNN and SVM: A Comparative Study with Traditional Diagnostic Methods
Kukana Hybrid Machine Learning Algorithm-Based Paddy Leave Disease Detection System
Tahir et al. A methodology of customized dataset for cotton disease detection using deep learning algorithms
Meena et al. Plant Diseases Detection Using Deep Learning
Li et al. A machine learning approach for detection plant disease: Taking orchid as example
Pravin et al. A identification of piper plant species based on deep learning networks
Zia et al. Analysis of grape leaf disease by using deep convolutional neural network
Lwin et al. Image classification for Rice leaf disease using AlexNet model
Singh et al. Plant disorder and disease detection using image processing
Singh et al. Plant Disease Detection using Convolution Neural Network Approach
Valarmathi et al. Fruit Disease Prediction with Fertilizer Recommendation for Citrus Family using Deep Learning
Sharmila et al. Cotton Leaf Disease Detection using Convolutional Neural Networks (CNN)