Classification of rice varieties with deep learning methods

Multiclass classification of dry beans using computer vision and machine learning techniques

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A Novel Basketball Result Prediction Model Using a Concurrent Neuro-Fuzzy System

(2020) Ilker Ali Ozkan   APPLIED ARTIFICIAL INTELLIGENCE

Brain tumor classification using deep CNN features via transfer learning

(2019) S. Deepak et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Towards a real-time sorting system: Identification of vitreous durum wheat kernels using ANN based on their morphological, colour, wavelet and gaborlet features

(2019) Esra Kaya et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat

(2019) Nastasiya F. Grinberg et al.   MACHINE LEARNING

A Deep Convolutional Neural Network Architecture for Boosting Image Discrimination Accuracy of Rice Species

(2018) P. Lin et al.   Food and Bioprocess Technology

A computer vision approach based on endocarp features for the identification of olive cultivars

(2018) S. Satorres Martínez et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review

(2018) Diego Inácio Patrício et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A survey of deep neural network architectures and their applications

(2017) Weibo Liu et al.   NEUROCOMPUTING

A real-time phenotyping framework using machine learning for plant stress severity rating in soybean

(2017) Hsiang Sing Naik et al.   Plant Methods

A two-camera machine vision approach to separating and identifying laboratory sprouted wheat kernels

(2016) Bijay L. Shrestha et al.   BIOSYSTEMS ENGINEERING

A shadow-based method to calculate the percentage of filled rice grains

(2016) Tao Liu et al.   BIOSYSTEMS ENGINEERING

A review on the main challenges in automatic plant disease identification based on visible range images

(2016) Jayme Garcia Arnal Barbedo   BIOSYSTEMS ENGINEERING

Detection of aphids in wheat fields using a computer vision technique

(2016) Tao Liu et al.   BIOSYSTEMS ENGINEERING

Local descriptors for soybean disease recognition

(2016) Rillian Diello Lucas Pires et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Wheat grain classification by using dense SIFT features with SVM classifier

(2016) Murat Olgun et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Computer vision-based method for classification of wheat grains using artificial neural network

(2016) Kadir Sabanci et al.   JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE

Deep learning for visual understanding: A review

(2016) Yanming Guo et al.   NEUROCOMPUTING

Image acquisition techniques for assessment of legume quality

(2015) Shveta Mahajan et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

Potential Applications of Computer Vision in Quality Inspection of Rice: A Review

(2015) Hemad Zareiforoush et al.   Food Engineering Reviews

Evaluation and analysis the chalkiness of connected rice kernels based on image processing technology and support vector machine

(2014) Chengming Sun et al.   JOURNAL OF CEREAL SCIENCE

Toward an automatic wheat purity measuring device: A machine vision-based neural networks-assisted imperialist competitive algorithm approach

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Artificial neural network modeling of the river water quality—A case study

(2009) Kunwar P. Singh et al.   ECOLOGICAL MODELLING

A systematic analysis of performance measures for classification tasks

(2009) Marina Sokolova et al.   INFORMATION PROCESSING & MANAGEMENT

Logistic Regression

(2008) Michael P. LaValley   CIRCULATION