Gökçer, Türkan YelizAslan, İsmail2024-06-132024-06-1320220096-30031873-564910.1016/j.amc.2022.1270112-s2.0-85124648426https://doi.org/10.1016/j.amc.2022.127011https://hdl.handle.net/11501/1138In this study, we construct Kantorovich variant of max-min kind operators, which are nonlinear. By using these new operators, we obtain some uniform approximation results in N dimension ( N >= 1 ). Then, we estimate the error with the help of Holder continuous functions and modulus of continuity. Furthermore, we give some illustrative applications to verify our theory and also investigate some shape-preserving properties of Kantorovichtype max-min Bernstein operator. Lastly, we examine the image processing implementation of our results via Kantorovich-type max-min Shepard operator.eninfo:eu-repo/semantics/closedAccessMax-Min OperatorsKantorovich OperatorsRate of ApproximationShape-Preserving PropertiesFuzzy LogicImage ProcessingArticleQ1423WOS:000779185700006Q1