A novel method based on machine vision system and deep learning to detect fraud in turmeric powder

Surface color distribution analysis by computer vision compared to sensory testing: Vacuum fried fruits as a case study

(2021) Fitriyono Ayustaningwarno et al.   FOOD RESEARCH INTERNATIONAL

Development of a hybrid system based on convolutional neural networks and support vector machines for recognition and tracking color changes in food during thermal processing

(2021) Weskley da Silva Cotrim et al.   CHEMICAL ENGINEERING SCIENCE

Rapid identification of chrysanthemum teas by computer vision and deep learning

(2020) Chunlin Liu et al.   Food Science & Nutrition

Deep thermal imaging to compute the adulteration state of extra virgin olive oil

(2020) Manuel Izquierdo et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Potential of deep learning and snapshot hyperspectral imaging for classification of species in meat

(2020) Mahmoud Al-Sarayreh et al.   FOOD CONTROL

Microencapsulation of pomegranate (Punica granatum L.) seed oil by complex coacervation: Development of a potential functional ingredient for food application

(2020) André M.M. Costa et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Evaluation of image processing technique and discriminant analysis methods in postharvest processing of carrot fruit

(2020) Ahmad Jahanbakhshi et al.   Food Science & Nutrition

Discussion of: “Nonparametric regression using deep neural networks with ReLU activation function”

(2020) Gitta Kutyniok   ANNALS OF STATISTICS

Extracting apple tree crown information from remote imagery using deep learning

(2020) Jintao Wu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Raman and IR spectroscopic modality for authentication of turmeric powder

(2020) Kuanglin Chao et al.   FOOD CHEMISTRY

A microcontroller based machine vision approach for tomato grading and sorting using SVM classifier

(2020) S. Dhakshina Kumar et al.   MICROPROCESSORS AND MICROSYSTEMS

Evaluation of image processing technique as an expert system in mulberry fruit grading based on ripeness level using artificial neural networks (ANNs) and support vector machine (SVM)

(2020) Hossein Azarmdel et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Accurate classification of cherry fruit using deep CNN based on hybrid pooling approach

(2020) Mohammad Momeny et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Food fraud vulnerability assessment: Towards a global consensus on procedures to manage and mitigate food fraud

(2020) Virginie Barrere et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network

(2020) Omer Deperlioglu et al.   COMPUTER COMMUNICATIONS

Real or fake yellow in the vibrant colour craze: Rapid detection of lead chromate in turmeric

(2020) Sara W. Erasmus et al.   FOOD CONTROL

Artificial intelligence-based identification of butter variations as a model study for detecting food adulteration

(2020) Gokce Iymen et al.   Innovative Food Science & Emerging Technologies

Rapid detection of green‐pea adulteration in pistachio nuts using Raman spectroscopy and chemometrics

(2020) Osman Taylan et al.   JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE

Minor blind feature based Steganalysis for calibrated JPEG images with cross validation and classification using SVM and SVM-PSO

(2020) Deepa D. Shankar et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Convolutional Neural Networks for individual identification in the Southern Rock Lobster supply chain

(2020) Son Anh Vo et al.   FOOD CONTROL

Real-Time Moisture Ratio Study of Drying Date Fruit Chips Based on On-Line Image Attributes Using kNN and Random Forest Regression Methods

(2020) Madi Keramat-Jahromi et al.   MEASUREMENT

A simple and quick method to detect adulterated sesame oil using 3D fluorescence spectra

(2020) Zhao Pan et al.   SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY

Turmeric / curcumin and health outcomes: A meta-review of systematic reviews

(2020) Vivien Rolfe et al.   European Journal of Integrative Medicine

Early warning and control of food safety risk using an improved AHC-RBF neural network integrating AHP-EW

(2020) Zhiqiang Geng et al.   JOURNAL OF FOOD ENGINEERING

Emerging non-destructive methods for quality and safety monitoring of spices

(2020) Nikitha Modupalli et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

Detecting cooking state of grilled chicken by electronic nose and computer vision techniques

(2020) Fedor S. Fedorov et al.   FOOD CHEMISTRY

CaneSat dataset to leverage convolutional neural networks for sugarcane classification from Sentinel-2

(2020) Shyamal S. Virnodkar et al.   Journal of King Saud University-Computer and Information Sciences

Hyperspectral fruit and vegetable classification using convolutional neural networks

(2019) Jan Steinbrener et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Application of Deep Learning in Food: A Review

(2019) Lei Zhou et al.   COMPREHENSIVE REVIEWS IN FOOD SCIENCE AND FOOD SAFETY

Application of an olfactory system to detect and distinguish bitter chocolates with different percentages of cocoa

(2019) Behzad Nouri et al.   JOURNAL OF FOOD PROCESS ENGINEERING

Conventional models and artificial intelligence-based models for energy consumption forecasting: A review

(2019) Nan Wei et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Convolutional decoding of thermographic images to locate and quantify honey adulterations

(2019) Manuel Izquierdo et al.   TALANTA

Validation of multispectral imaging for the detection of selected adulterants in turmeric samples

(2019) Wele Gedara Chaminda Bandara et al.   JOURNAL OF FOOD ENGINEERING

Classification of sour lemons based on apparent defects using stochastic pooling mechanism in deep convolutional neural networks

(2019) Ahmad Jahanbakhshi et al.   SCIENTIA HORTICULTURAE

Deep learning in agriculture: A survey

(2018) Andreas Kamilaris et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Generalizing Pooling Functions in CNNs: Mixed, Gated, and Tree

(2018) Chen-Yu Lee et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Using an E-nose machine for detection the adulteration of margarine in cow ghee

(2018) Fardin Ayari et al.   JOURNAL OF FOOD PROCESS ENGINEERING

Partial Least Squares Regression (PLSR) Applied to NIR and HSI Spectral Data Modeling to Predict Chemical Properties of Fish Muscle

(2016) Jun-Hu Cheng et al.   Food Engineering Reviews