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Prediction modeling using deep learning for the classification of grape-type dried fruits


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Cinar I., Koklu M., Classification of rice varieties using artificial intelligence methods, International Journal of Intelligent Systems and Applications in Engineering, 7(3), 188–194, 2019. CinarI. KokluM. Classification of rice varieties using artificial intelligence methods International Journal of Intelligent Systems and Applications in Engineering 7 3 188 194 2019 Search in Google Scholar

Şapaloğlu A., The Structure of the Marketing Channels and Rice Marketing Margins in the Chain of Rice Production-Consumption: An Example of Edirne Province, MSc. Thesis, Namik Kemal University, Tekirdağ, Türkiye, 2015. ŞapaloğluA. The Structure of the Marketing Channels and Rice Marketing Margins in the Chain of Rice Production-Consumption: An Example of Edirne Province MSc. Thesis, Namik Kemal University Tekirdağ, Türkiye 2015 Search in Google Scholar

Semerci A., Kiziltuğ T., Çelik A.D., Kiraci M.A., General overview of viticulture in Turkey, Journal of Mustafa Kemal University Faculty of Agriculture, 20(2), 42–51, 2015. SemerciA. KiziltuğT. ÇelikA.D. KiraciM.A. General overview of viticulture in Turkey Journal of Mustafa Kemal University Faculty of Agriculture 20 2 42 51 2015 Search in Google Scholar

Cinar I., Koklu M., Tasdemir S., Classification of raisin grains using machine vision and artificial intelligence methods, Gazi Journal of Engineering Sciences, 6(3), 200–209, 2020. CinarI. KokluM. TasdemirS. Classification of raisin grains using machine vision and artificial intelligence methods Gazi Journal of Engineering Sciences 6 3 200 209 2020 Search in Google Scholar

Sammut S.J., Crispin-Ortuzar M., Chin S.F., Provenzano E., Bardwell H.A., Ma W., Cope W., Dariush A., Dawson S.J., Abraham J.E., Dunn J., Hiller L., Thomas J., Cameron D.A., Bartlett J.M.S., Hayward L., Pharoah P.D., Markowetz F., Rueda O.M., Earl H.M., Caldas C., Multi-omic machine learning predictor of breast cancer therapy response, Nature, 601(7894), 623–629, 2022. SammutS.J. Crispin-OrtuzarM. ChinS.F. ProvenzanoE. BardwellH.A. MaW. CopeW. DariushA. DawsonS.J. AbrahamJ.E. DunnJ. HillerL. ThomasJ. CameronD.A. BartlettJ.M.S. HaywardL. PharoahP.D. MarkowetzF. RuedaO.M. EarlH.M. CaldasC. Multi-omic machine learning predictor of breast cancer therapy response Nature 601 7894 623 629 2022 Search in Google Scholar

Chaulagain R.S., Liza F.T., Chunduri S., Yuan X., Lang M., Achieving the performance of global adaptive routing using local information on dragonfly through deep learning, ACM/IEEE SC Tech Poster, 1–3, 2020. ChaulagainR.S. LizaF.T. ChunduriS. YuanX. LangM. Achieving the performance of global adaptive routing using local information on dragonfly through deep learning ACM/IEEE SC Tech Poster 1 3 2020 Search in Google Scholar

Yao Z., Lum Y., Johnston A., Mejia-Mendoza L.M., Zhou X., Wen Y., Aspuru-Guzik A., Sargent E.H., Seh Z.W., Machine learning for a sustainable energy future, Nature Reviews Materials, 8(3), 202–215, 2023. YaoZ. LumY. JohnstonA. Mejia-MendozaL.M. ZhouX. WenY. Aspuru-GuzikA. SargentE.H. SehZ.W. Machine learning for a sustainable energy future Nature Reviews Materials 8 3 202 215 2023 Search in Google Scholar

Khan M., Das R.C., Casey J., Reese B.L., Akintunde B., Pathak A.K., Near room temperature magnetocaloric properties in Ni deficient (Mn0.525Fe0.5) Ni0.975 Si0.95AI0.05, AIP Advances, 12(035227), 1–5, 2022. KhanM. DasR.C. CaseyJ. ReeseB.L. AkintundeB. PathakA.K. Near room temperature magnetocaloric properties in Ni deficient (Mn0.525Fe0.5) Ni0.975 Si0.95AI0.05 AIP Advances 12 035227 1 5 2022 Search in Google Scholar

Stein I., Raihen M.N., Convergence rates for Hestenes’ Gram–Schmidt conjugate direction method without derivatives in numerical optimization, AppliedMath, 3, 268–285, 2023. SteinI. RaihenM.N. Convergence rates for Hestenes’ Gram–Schmidt conjugate direction method without derivatives in numerical optimization AppliedMath 3 268 285 2023 Search in Google Scholar

Baykan Ö.K, Babalik A., Botsali F.M., Recognition of wheat species using artificial neural network, 4 International Symposium on Advanced Technologies, Konya, Türkiye, 28–30 September 2005, 188–190. BaykanÖ.K BabalikA. BotsaliF.M. Recognition of wheat species using artificial neural network 4 International Symposium on Advanced Technologies Konya, Türkiye 28–30 September 2005 188 190 Search in Google Scholar

Amin M.Z., Ali A., Performance evaluation of supervised machine learning classifiers for predicting healthcare operational decisions, Technical Report, DOI: 10.13140/RG.2.2.26371.25127, 1–7, 2017. AminM.Z. AliA. Performance evaluation of supervised machine learning classifiers for predicting healthcare operational decisions Technical Report, 10.13140/RG.2.2.26371.25127 1 7 2017 Open DOISearch in Google Scholar

Valiente C., Arrigoni E., Esteban R.M., Amado R., Grape pomace as a potential food fiber, Journal of Food Science, 60(4), 818–820, 1995. ValienteC. ArrigoniE. EstebanR.M. AmadoR. Grape pomace as a potential food fiber Journal of Food Science 60 4 818 820 1995 Search in Google Scholar

Martin-Carron N., Garcia-Alonso A., Goñi I., Saura-Calixto F., Nutritional and physiological properties of grape pomace as a potential food ingredient, American Journal of Enology and Viticulture, 48(3), 328–332, 1997. Martin-CarronN. Garcia-AlonsoA. GoñiI. Saura-CalixtoF. Nutritional and physiological properties of grape pomace as a potential food ingredient American Journal of Enology and Viticulture 48 3 328 332 1997 Search in Google Scholar

Yeung C.K., Glahn R.P., Wu X., Liu R.H., Miller D.D., In vitro iron bioavailability and antioxidant activity of raisins, Journal of Food Science, 68(2), 701–705, 2003. YeungC.K. GlahnR.P. WuX. LiuR.H. MillerD.D. In vitro iron bioavailability and antioxidant activity of raisins Journal of Food Science 68 2 701 705 2003 Search in Google Scholar

Karimi N., Kondrood R.R., Alizadeh T., An intelligent system for quality measurement of Golden Bleached raisins using two comparative machine learning algorithms, Measurement, 107, 68–76, 2017. KarimiN. KondroodR.R. AlizadehT. An intelligent system for quality measurement of Golden Bleached raisins using two comparative machine learning algorithms Measurement 107 68 76 2017 Search in Google Scholar

Mollazade K., Omid M., Arefi A., Comparing data mining classifiers for grading raisins based on visual features, Computers and Electronics in Agriculture, 84, 124–131, 2012. MollazadeK. OmidM. ArefiA. Comparing data mining classifiers for grading raisins based on visual features Computers and Electronics in Agriculture 84 124 131 2012 Search in Google Scholar

Zareiforoush H., Minaei S., Alizadeh M.R., Banakar A., A hybrid intelligent approach based on computer vision and fuzzy logic for quality measurement of milled rice, Measurement, 66, 26–34, 2015. ZareiforoushH. MinaeiS. AlizadehM.R. BanakarA. A hybrid intelligent approach based on computer vision and fuzzy logic for quality measurement of milled rice Measurement 66 26 34 2015 Search in Google Scholar

Okamura N.K., Delwiche M.J., Thompson J.F., Raisin grading by machine vision, Transactions of the ASAE, 36(2), 485–492, 1993. OkamuraN.K. DelwicheM.J. ThompsonJ.F. Raisin grading by machine vision Transactions of the ASAE 36 2 485 492 1993 Search in Google Scholar

Dirik M., Improving raisin grains classification with a hybrid PSO-NN approach, 1st International Conference on Contemporary Academic Research (ICCAR 2023), 17–19 May 2023, Konya, Türkiye, 1, 34–41, 2023. DirikM. Improving raisin grains classification with a hybrid PSO-NN approac 1st International Conference on Contemporary Academic Research (ICCAR 2023) 17–19 May 2023 Konya, Türkiye 1 34 41 2023 Search in Google Scholar

Raihen N., Akter S., Forecasting breast cancer: A study of classifying patients’ post-surgical survival rates with breast cancer, Biomedical Journal of Scientific and Technical Research, 50(1), 41310–41319, 2023. RaihenN. AkterS. Forecasting breast cancer: A study of classifying patients’ post-surgical survival rates with breast cancer Biomedical Journal of Scientific and Technical Research 50 1 41310 41319 2023 Search in Google Scholar

Omid M., Abbasgolipour M., Keyhani A., Mohtasebi S.S., Implementation of an efficient image processing algorithm for grading raisins, International Journal of Signal and Image Processing, 1(1), 31–34, 2010. OmidM. AbbasgolipourM. KeyhaniA. MohtasebiS.S. Implementation of an efficient image processing algorithm for grading raisins International Journal of Signal and Image Processing 1 1 31 34 2010 Search in Google Scholar

Tarakci F., Ozkan I.A., Comparison of classification performance of kNN and WKNN algorithms, Selcuk University Journal of Engineering Sciences, 20(02), 32–37, 2021. TarakciF. OzkanI.A. Comparison of classification performance of kNN and WKNN algorithms Selcuk University Journal of Engineering Sciences 20 02 32 37 2021 Search in Google Scholar

Unal Y., Kaplan H., Bektas Y., Caglar M.B., Classification of raisin grains variety using some machine learning methods, New Trends in Computer Sciences, 1(1), 62–69, 2023. UnalY. KaplanH. BektasY. CaglarM.B. Classification of raisin grains variety using some machine learning methods New Trends in Computer Sciences 1 1 62 69 2023 Search in Google Scholar

Angadi S.A., Hiregoudar N., A cost effective algorithm for grading raisins using image processing, International Journal of Recent Trends in Engineering Research, 2, 2455–2457, 2016. AngadiS.A. HiregoudarN. A cost effective algorithm for grading raisins using image processing International Journal of Recent Trends in Engineering Research 2 2455 2457 2016 Search in Google Scholar

Khojastehnazhand M., Ramezani H., Machine vision system for classification of bulk raisins using texture features, Journal of Food Engineering, 271, 109864, 2020. KhojastehnazhandM. RamezaniH. Machine vision system for classification of bulk raisins using texture features Journal of Food Engineering 271 109864 2020 Search in Google Scholar

Hu M.H., Dong Q.L., Liu B.L., Malakar P.K., The potential of double K-means clustering for banana image segmentation, Journal of Food Process Engineering, 37(1), 10–18, 2014. HuM.H. DongQ.L. LiuB.L. MalakarP.K. The potential of double K-means clustering for banana image segmentation Journal of Food Process Engineering 37 1 10 18 2014 Search in Google Scholar

Kirkos E., Spathis C., Manolopoulos Y., Data mining techniques for the detection of fraudulent financial statements, Expert Systems with Applications, 32(4), 995–1003, 2007. KirkosE. SpathisC. ManolopoulosY. Data mining techniques for the detection of fraudulent financial statements Expert Systems with Applications 32 4 995 1003 2007 Search in Google Scholar

Raihen M.N.I., A Bifurcation Phenomenon of Regularized Free Boundary Problems of Two-Phase Elliptic-Parabolic Type, Ph.D. Thesis, Wayne State University, USA, 2022. RaihenM.N.I. A Bifurcation Phenomenon of Regularized Free Boundary Problems of Two-Phase Elliptic-Parabolic Type Ph.D. Thesis, Wayne State University USA 2022 Search in Google Scholar

Francis F.J., Clydesdale F.M., Food Colorimetry: Theory and Applications, AVI Publishing, USA, 1975. FrancisF.J. ClydesdaleF.M. Food Colorimetry: Theory and Applications AVI Publishing USA 1975 Search in Google Scholar

Koklu M., Sarigil S., Ozbek O., The use of machine learning methods in classification of pumpkin seeds (Cucurbita pepo L.), Genetic Resources and Crop Evolution, 68(7), 2713–2726, 2021. KokluM. SarigilS. OzbekO. The use of machine learning methods in classification of pumpkin seeds (Cucurbita pepo L.) Genetic Resources and Crop Evolution 68 7 2713 2726 2021 Search in Google Scholar

U.C.M.Learning, “Raisin Grains Dataset”, March, 2020 [online], available: https://www.muratkoklu.com/datasets/, Accessed: 05 July, 2023. U.C.M.Learning “Raisin Grains Dataset” March 2020 [online], available: https://www.muratkoklu.com/datasets/, Accessed: 05 July, 2023. Search in Google Scholar

Jain S., Shukla S., Wadhvani R., Dynamic selection of normalization techniques using data complexity measures, Expert Systems with Applications, 106, 252–262, 2018. JainS. ShuklaS. WadhvaniR. Dynamic selection of normalization techniques using data complexity measures Expert Systems with Applications 106 252 262 2018 Search in Google Scholar

Raihen M.N., Akter S., Tabassum F., Jahan F., Sardar M.N., A statistical analysis of positive excess mortality at Covid-19 in 2020–2021, Journal of Mathematics and Statistics Studies, 4(3), 07–17, 2023. RaihenM.N. AkterS. TabassumF. JahanF. SardarM.N. A statistical analysis of positive excess mortality at Covid-19 in 2020–2021 Journal of Mathematics and Statistics Studies 4 3 07 17 2023 Search in Google Scholar

Raihen M.N., Akter S., Sardar M.N., Food satisfaction among students: A study of present public university students in Bangladesh, Journal of Mathematics and Statistics Studies, 4(1), 1–18, 2023. RaihenM.N. AkterS. SardarM.N. Food satisfaction among students: A study of present public university students in Bangladesh Journal of Mathematics and Statistics Studies 4 1 1 18 2023 Search in Google Scholar

Khoshroo A., Arefi A., Masoumiasl A., Jowkar G.H., Classification of wheat cultivars using image processing and artificial neural networks, Agricultural Communications, 2(1), 17–22, 2014. KhoshrooA. ArefiA. MasoumiaslA. JowkarG.H. Classification of wheat cultivars using image processing and artificial neural networks Agricultural Communications 2 1 17 22 2014 Search in Google Scholar

Bergmeir C., Benítez J.M., Forecaster performance evaluation with cross-validation and variants, 2011 11th International Conference on Intelligent Systems Design and Applications, IEEE, Cordoba, Spain, 849–854, 2011. BergmeirC. BenítezJ.M. Forecaster performance evaluation with cross-validation and variants 2011 11th International Conference on Intelligent Systems Design and Applications, IEEE Cordoba, Spain 849 854 2011 Search in Google Scholar

Altay O., Ulas M., Alyamac K.E., Prediction of the fresh performance of steel fiber reinforced self-compacting concrete using quadratic SVM and weighted KNN models, IEEE Access, 8, 92647–92658, 2020. AltayO. UlasM. AlyamacK.E. Prediction of the fresh performance of steel fiber reinforced self-compacting concrete using quadratic SVM and weighted KNN models IEEE Access 8 92647 92658 2020 Search in Google Scholar

Omar N., Al-zebari A., Sengur A., Deep learning approach to predict forest fires using meteorological measurements, 2021 2nd International Informatics and Software Engineering Conference, IEEE, Ankara, Türkiye, 1–4, 2021. OmarN. Al-zebariA. SengurA. Deep learning approach to predict forest fires using meteorological measurements 2021 2nd International Informatics and Software Engineering Conference, IEEE Ankara, Türkiye 1 4 2021 Search in Google Scholar

Raihen M.N, Akter S., Sardar M.N., Women’s career challenges and opportunities (A study of career and job satisfaction among Bangladeshi Women), Academic Journal of Research and Scientific Publishing, 5(51), 05–22, 2023. RaihenM.N AkterS. SardarM.N. Women’s career challenges and opportunities (A study of career and job satisfaction among Bangladeshi Women) Academic Journal of Research and Scientific Publishing 5 51 05 22 2023 Search in Google Scholar

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