An Improved Classification of Pork Adulteration in Beef Based on Electronic Nose Using Modified Deep Extreme Learning with Principal Component Analysis as Feature Learning

Automatic Detection and Classification of Mammograms Using Improved Extreme Learning Machine with Deep Learning

(2021) S.R. Sannasi Chakravarthy et al.   IRBM

Food Allergy Prevention: More Than Peanut

(2020) Michael R. Perkin et al.   Journal of Allergy and Clinical Immunology-In Practice

EXPRESS: Signal Enhancement Evaluation of Laser Induced Breakdown Spectroscopy of Extracted Animal Fats Using a Principal Component Analysis Approach

(2020) Nur Syaida Hanasil et al.   APPLIED SPECTROSCOPY

Detection of Volatiles in Dark Chocolate Flavored with Orange Essential Oil by Electronic Nose

(2020) Elisiane Galvagni et al.   Food Analytical Methods

SPR Enhanced DNA Biosensor for Sensitive Detection of Donkey Meat Adulteration

(2020) Maryam Mansouri et al.   FOOD CHEMISTRY

Characterization of flavor volatile compounds in sauce spareribs by gas chromatography–mass spectrometry and electronic nose

(2020) Jie Shi et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Densely Connected Deep Extreme Learning Machine Algorithm

(2020) X. W. Jiang et al.   Cognitive Computation

A comprehensive review of food fraud terminologies and food fraud mitigation guides

(2020) Kelsey Robson et al.   FOOD CONTROL

Deep extreme learning machine with leaky rectified linear unit for multiclass classification of pathological brain images

(2019) Deepak Ranjan Nayak et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Noise filtering framework for electronic nose signals: An application for beef quality monitoring

(2019) Dedy Rahman Wijaya et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Interpreting and Reporting Principal Component Analysis in Food Science Analysis and Beyond

(2019) D. Cozzolino et al.   Food Analytical Methods

Peach growth cycle monitoring using an electronic nose

(2019) Henike Guilherme Jordan Voss et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Automatic Detection and Grading of Multiple Fruits by Machine Learning

(2019) Anuja Bhargava et al.   Food Analytical Methods

Lipid oxidation degree of pork meat during frozen storage investigated by near-infrared hyperspectral imaging: Effect of ice crystal growth and distribution

(2019) Weiwei Cheng et al.   JOURNAL OF FOOD ENGINEERING

Performance Comparison of Support Vector Machine, Random Forest, and Extreme Learning Machine for Intrusion Detection

(2018) Iftikhar Ahmad et al.   IEEE Access

A novel method using MOS electronic nose and ELM for predicting postharvest quality of cherry tomato fruit treated with high pressure argon

(2018) Lei Feng et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Adulterant identification in mutton by electronic nose and gas chromatography-mass spectrometer

(2018) Qian Wang et al.   FOOD CONTROL

Evaluation of Industrial Roasting Degree of Coffee Beans by Using an Electronic Nose and a Stepwise Backward Selection of Predictors

(2017) P. Giungato et al.   Food Analytical Methods

Identification of Pork Adulteration in Processed Meat Products Using the Developed Mitochondrial DNA-Based Primers

(2017) Jimyeong Ha et al.   Korean Journal for Food Science of Animal Resources

Mining Feature of Data Fusion in the Classification of Beer Flavor Information Using E-Tongue and E-Nose

(2017) et al.   SENSORS

Immuno strip test for detection of pork adulteration in cooked meatballs

(2017) Bambang Kuswandi et al.   Food Bioscience

Classification and regression of ELM, LVQ and SVM for E-nose data of strawberry juice

(2015) Shanshan Qiu et al.   JOURNAL OF FOOD ENGINEERING

Deep Extreme Learning Machine and Its Application in EEG Classification

(2015) Shifei Ding et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Classification of Rice by Combining Electronic Tongue and Nose

(2014) Lin Lu et al.   Food Analytical Methods

Fuji Apple Storage Time Predictive Method Using Electronic Nose

(2012) Hui Guohua et al.   Food Analytical Methods

Rapid identification of pork for halal authentication using the electronic nose and gas chromatography mass spectrometer with headspace analyzer

(2011) M. Nurjuliana et al.   MEAT SCIENCE