4.3 Article

Developing a deep neural network model for predicting carrots volume

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Information Systems

Volumetric estimation using 3D reconstruction method for grading of fruits

Tushar Jadhav et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2019)

Article Engineering, Chemical

Tomato volume and mass estimation using computer vision and machine learning algorithms: Cherry tomato model

Innocent Nyalala et al.

JOURNAL OF FOOD ENGINEERING (2019)

Article Agriculture, Multidisciplinary

A computer vision system for defect discrimination and grading in tomatoes using machine learning and image processing

David Ireri et al.

ARTIFICIAL INTELLIGENCE IN AGRICULTURE (2019)

Article Computer Science, Information Systems

A survey of deep learning-based network anomaly detection

Donghwoon Kwon et al.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2019)

Article Agriculture, Multidisciplinary

A methodology for fresh tomato maturity detection using computer vision

Peng Wan et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)

Article Computer Science, Artificial Intelligence

Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models

Ha Young Kim et al.

EXPERT SYSTEMS WITH APPLICATIONS (2018)

Article Agricultural Engineering

Developing predictive models for determining physical properties of coffee beans during the roasting process

Jaime Daniel Bustos-Vanegas et al.

INDUSTRIAL CROPS AND PRODUCTS (2018)

Article Computer Science, Artificial Intelligence

A survey on deep learning for big data

Qingchen Zhang et al.

INFORMATION FUSION (2018)

Article Agricultural Engineering

Detection of passion fruits and maturity classification using Red-Green-Blue Depth images

Shuqin Tu et al.

BIOSYSTEMS ENGINEERING (2018)

Article Food Science & Technology

Modeling of volume and surface area of apple from their geometric characteristics and artificial neural network

Armin Ziaratban et al.

INTERNATIONAL JOURNAL OF FOOD PROPERTIES (2017)

Review Radiology, Nuclear Medicine & Medical Imaging

Toolkits and Libraries for Deep Learning

Bradley J. Erickson et al.

JOURNAL OF DIGITAL IMAGING (2017)

Article Agricultural Engineering

Class-based physical properties of air-classified sunflower seeds and kernels

Simon Munder et al.

BIOSYSTEMS ENGINEERING (2017)

Article Engineering, Multidisciplinary

Computational mechanics enhanced by deep learning

Atsuya Oishi et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2017)

Review Automation & Control Systems

A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation

Bo Zhao et al.

INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING (2017)

Article Chemistry, Applied

Physical and chemical properties of pomegranate fruit accessions from Croatia

Mira Radunic et al.

FOOD CHEMISTRY (2015)

Review Multidisciplinary Sciences

Deep learning

Yann LeCun et al.

NATURE (2015)

Article Computer Science, Artificial Intelligence

A deep analysis on age estimation

Ivan Huerta et al.

PATTERN RECOGNITION LETTERS (2015)

Article Computer Science, Information Systems

A deep learning approach to the classification of 3D CAD models

Fei-wei Qin et al.

JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE C-COMPUTERS & ELECTRONICS (2014)

Article Agriculture, Multidisciplinary

Influence of Drying by Convective Air Dryer or Power Ultrasound on the Vitamin C and β-Carotene Content of Carrots

Juana Frias et al.

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY (2010)

Article Agriculture, Multidisciplinary

Modeling of tomato drying using artificial neural network

Kamyar Movagharnejad et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2007)

Article Engineering, Chemical

Drying curve modelling of blanched carrot cubes under natural convection condition

K. Gornicki et al.

JOURNAL OF FOOD ENGINEERING (2007)

Article Chemistry, Applied

Predicting oxidative stability of vegetable oils using neural network system and endogenous oil components

R Przybylski et al.

JOURNAL OF THE AMERICAN OIL CHEMISTS SOCIETY (2000)