Book ChapterDOI
A Review on Agricultural Advancement Based on Computer Vision and Machine Learning
Abriti Paul,Sourav Ghosh,Amit Kumar Das,Saptarsi Goswami,Sruti Das Choudhury,Soumya Sen +5 more
- pp 567-581
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TLDR
This review paper gives an overview of machine learning and computer vision techniques which are inherently associated with this domain and tries to give an analysis, which can help researchers to look at some relevant problems in the context of India.Abstract:
The importance of agriculture in modern society need not be overstated. In order to meet the huge requirements of food and to mitigate, the conventional problems of cropping smart and sustainable agriculture have emerged over the conventional agriculture. From computational perspective, computer vision and machine learning techniques have been applied in many aspects of human and social life, and agriculture is not also an exception. This review paper gives an overview of machine learning and computer vision techniques which are inherently associated with this domain. A summary of the works highlighting different seeds, crops, fruits with the country is also enclosed. The paper also tries to give an analysis, which can help researchers to look at some relevant problems in the context of India.read more
Citations
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Journal ArticleDOI
Insect pest monitoring with camera-equipped traps: strengths and limitations
TL;DR: The purpose of this review is to summarize the progress made on automatic traps with a particular focus on camera-equipped traps to support the use of software and image recognition algorithms to identify and/or count insect species from pictures.
Journal ArticleDOI
A novel deep learning method for detection and classification of plant diseases
TL;DR: A robust plant disease classification system is introduced by introducing a Custom CenterNet framework with DenseNet-77 as a base network and is more proficient and reliable to identify and classify plant diseases than other latest approaches.
Book ChapterDOI
Visual Product Inspection Based on Deep Learning Methods
TL;DR: The present article deals with the above-mentioned method of deep learning, and especially with its application when recognizing certain objects and elements during the visual product inspection.
Journal ArticleDOI
Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts
Gayatri Mishra,Brajesh Kumar Panda,Wilmer Ariza Ramirez,Hye-Won Jung,Chandra B. Singh,Chandra B. Singh,Sang-Heon Lee,Ivan Lee +7 more
TL;DR: In this article, a review summarizes the recent application of rapid and nondestructive optical imaging and spectroscopic techniques, including digital color imaging, X-ray imaging, near-infrared spectroscopy, fluorescent, multispectral, and hyperspectral imaging.
Journal ArticleDOI
Evaluation of Efficacy of Fungicides for Control of Wheat Fusarium Head Blight Based on Digital Imaging
TL;DR: A new method to rapidly assess the severity of FHB and evaluate the efficacy of fungicide application programs and the results show that the segmentation algorithm could segment wheat ears from a complex field background and the counting algorithm could effectively solve the problem of wheat ear adhesion and occlusion.
References
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Journal ArticleDOI
Ensemble data mining approaches to forecast regional sugarcane crop production.
TL;DR: In this paper, hundreds of model settings (models for convenience) that represent different environmental and management conditions were created for Ayr, a major sugarcane growing region in north eastern Australia.
Proceedings ArticleDOI
A review of the application of data mining techniques for decision making in agriculture
Niketa Gandhi,Leisa Armstrong +1 more
TL;DR: This review proposes that further investigations are needed to understand how artificial neural networks, Bayesian networks, and support vector machines can be used with complex agricultural datasets for crop yield prediction integrating seasonal and spatial factors by using GIS technologies.
Journal ArticleDOI
Multicolor Fluorescence Imaging as a Candidate for Disease Detection in Plant Phenotyping.
TL;DR: This work evaluates the possible application of multicolor fluorescence imaging in combination with thermography for the particular case of zucchini plants affected by soft-rot, caused by Dickeya dadantii, and finds that MCFI in combinationWith thermography prove useful at providing data at lab scale that can be analyzed by machine learning.
Journal ArticleDOI
A Comparative Study on Application of Computer Vision and Fluorescence Imaging Spectroscopy for Detection of Huanglongbing Citrus Disease in the USA and Brazil
Caio Bruno Wetterich,Ratnesh Kumar,Sindhuja Sankaran,José Belasque Junior,Reza Ehsani,Luís Gustavo Marcassa +5 more
TL;DR: The results indicated that the SVM could classify HLB-infected leaf fluorescence intensities with up to 90% classification accuracy and shows potential for detecting HLB.
Journal ArticleDOI
Machine vision system for the automatic segmentation of plants under different lighting conditions
TL;DR: A machine vision system based on hybrid artificial neural network-harmony search (ANN-HS) classifiers for the segmentation of different plants in different growth stages, different conditions of the day and one controlled state and different imaging situations and it can be claimed that this system is applicable in all machine vision systems related to fields and has high accuracy and speed.