A real-valued function f defined on a convex subset D of some normed linear space X is said to be inner y-convex w.r.t. some fixed roughness degree gamma 0 if there is a v belong [0, 1] such that sup(f((l-A)x0 + Ax1) - (1 - A)f(xo) - A(x1)) or = 0 holds for all xo, x1 belong D satisfying ||xo - x1|| = vy and -(1/v)xo + (1 + l/v)x1 belong D. The requirement of this kind of roughly generalized convex functions is very weak; nevertheless, they also possess properties similar to those of convex functions relative to their supremum. For instance, if an inner gamma-convex function defined on some bounded convex subset D of an inner product space attains its maximum, then it has maximizers at some strictly gamma-extreme points of D. In this paper, some sufficient conditions and examples for gamma-convex functions and several properties relative to the location of their maximizers are given.