Real-time moisture ratio study of drying date fruit chips based on on-line image attributes using kNN and random forest regression methods
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Mahdi Ghasemi-Varnamkhasti | Seyed Saeid Mohtasebi | Hossein Mousazadeh | Mahdi Keramat-Jahromi | Maryam Rahimi-Movassagh | S. Mohtasebi | M. Ghasemi-Varnamkhasti | Mahdi Keramat-Jahromi | H. Mousazadeh | Maryam Rahimi-Movassagh | M. Keramat-Jahromi
[1] P. Capilla,et al. Calculation of the color matching functions of digital cameras from their complete spectral sensitivities : Color imaging science , 2002 .
[2] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[3] Time and speed of fruit drying on batch fluid-beds , 2005 .
[4] Andy Liaw,et al. Classification and Regression by randomForest , 2007 .
[5] Raimondo Schettini,et al. A New Method for RGB to XYZ Transformation Based on Pattern Search Optimization , 2007, IEEE Transactions on Consumer Electronics.
[6] Zafer Erbay,et al. A Review of Thin Layer Drying of Foods: Theory, Modeling, and Experimental Results , 2010, Critical reviews in food science and nutrition.
[7] Holger R. Maier,et al. Data splitting for artificial neural networks using SOM-based stratified sampling , 2010, Neural Networks.
[8] M. A. Sutton,et al. Multi-scale Mechanical Characterization of Palmetto Wood using Digital Image Correlation to Develop a Template for Biologically-Inspired Polymer Composites , 2011 .
[9] M. A. Khan,et al. Machine vision system: a tool for quality inspection of food and agricultural products , 2012, Journal of Food Science and Technology.
[10] A. Esehaghbeygi,et al. Electrohydrodynamic (EHD) drying of tomato slices (Lycopersicon esculentum) , 2011 .
[11] Marco S. Reis,et al. Madeira wine ageing prediction based on different analytical techniques: UV–vis, GC-MS, HPLC-DAD , 2011 .
[12] Yudong Zhang,et al. Classification of Fruits Using Computer Vision and a Multiclass Support Vector Machine , 2012, Sensors.
[13] Soleiman Hosseinpour,et al. Application of computer vision technique for on-line monitoring of shrimp color changes during drying , 2013 .
[14] Kianoosh Pirnazari,et al. Quality assessment of electrohydrodynamic and microwave dehydrated banana slices , 2014 .
[15] Mahdi Ghasemi-Varnamkhasti,et al. Computer vision technology for real-time food quality assurance during drying process , 2014 .
[16] Michel Havet,et al. Mathematical modeling of hot air/electrohydrodynamic (EHD) drying kinetics of mushroom slices , 2014 .
[17] Václav Snásel,et al. Random Forests Based Classification for Crops Ripeness Stages , 2014, IBICA.
[18] Kianoosh Pirnazari,et al. Assessment of Quality Attributes of Banana Slices Dried by Different Drying Methods , 2014 .
[19] Mahdi Ghasemi-Varnamkhasti,et al. Detecting maturity of persimmon fruit based on image processing technique , 2015 .
[20] M. Shahedi,et al. Quality assessment of mushroom slices dried by hot air combined with an electrohydrodynamic (EHD) drying system , 2015 .
[21] Soleiman Hosseinpour,et al. Continuous real-time monitoring and neural network modeling of apple slices color changes during hot air drying , 2015 .
[22] Soleiman Hosseinpour,et al. Computer Vision System (CVS) for In-Line Monitoring of Visual Texture Kinetics During Shrimp (Penaeus Spp.) Drying , 2015 .
[23] A. Martynenko,et al. Electrohydrodynamic drying of apple slices: Energy and quality aspects , 2016 .
[24] José Blasco,et al. Computer vision for automatic quality inspection of dried figs (Ficus carica L.) in real-time , 2016, Comput. Electron. Agric..
[25] Xinkai Zhu,et al. Estimation of biomass in wheat using random forest regression algorithm and remote sensing data , 2016 .
[26] Alex Martynenko,et al. Electrically-induced transport phenomena in EHD drying – A review , 2016 .
[27] Mahmoud Omid,et al. Real-time color change monitoring of apple slices using image processing during intermittent microwave convective drying , 2016, Food science and technology international = Ciencia y tecnologia de los alimentos internacional.
[28] Yuan-Yuan Pu,et al. Combined hot-air and microwave-vacuum drying for improving drying uniformity of mango slices based on hyperspectral imaging visualisation of moisture content distribution , 2017 .
[29] Alex Martynenko,et al. Improvement of kiwifruit drying using computer vision system (CVS) and ALM clustering method , 2017 .
[30] M. Mohebbi,et al. Application of Digital Image Processing in Monitoring some Physical Properties of Tarkhineh during Drying , 2017 .
[31] A. Martynenko,et al. Driving forces for mass transfer in electrohydrodynamic (EHD) drying , 2017 .
[32] Marcus Nagle,et al. Computer vision coupled with laser backscattering for non-destructive colour evaluation of papaya during drying , 2017, Journal of Food Measurement and Characterization.
[33] Ameneh Elmizadeh,et al. Comparison of electrohydrodynamic and hot-air drying of the quince slices , 2017 .
[34] Alex Martynenko,et al. Computer Vision for Real-Time Control in Drying , 2017, Food Engineering Reviews.
[35] Linyan Zhou,et al. Evaluation of browning ratio in an image analysis of apple slices at different stages of instant controlled pressure drop-assisted hot-air drying (AD-DIC). , 2017, Journal of the science of food and agriculture.
[36] Gennaro Cuccurullo,et al. Drying rate control in microwave assisted processing of sliced apples , 2018, Biosystems Engineering.
[37] Alexandros G. Dimakis,et al. AmbientGAN: Generative models from lossy measurements , 2018, ICLR.
[38] Seyed-Hassan Miraei Ashtiani,et al. Effects of hot-air and hybrid hot air-microwave drying on drying kinetics and textural quality of nectarine slices , 2018 .
[39] Sylvio Barbon Junior,et al. Predicting the ripening of papaya fruit with digital imaging and random forests , 2018, Comput. Electron. Agric..
[40] Sylvio Barbon Junior,et al. Computer Vision Classification of Barley Flour Based on Spatial Pyramid Partition Ensemble , 2019, Sensors.
[41] Akram Alomainy,et al. Machine Learning Driven Approach Towards the Quality Assessment of Fresh Fruits Using Non-Invasive Sensing , 2020, IEEE Sensors Journal.
[42] T. Ngo,et al. The use of digital image correlation for identifying failure characteristics of cross-laminated timber under transverse loading , 2020 .