Abstract: In a bead core, metal cords are accumulated and formed in plural columns and plural columns, and the row direction length is formed greater than the column direction length; the metal cords are set in two or more columns from the third row of the metal cords on as counted from a tire radial direction outer end inward in the tire radial direction and excepting a tire radial direction innermost end; a length dimension of the bead core is set equal to or greater than twice a maximum width dimension of the bead core; the centroid of the bead core is positioned on the tire radial direction inner end side of the bead core relative to the lengthwise direction center portion of the bead core; a maximum width portion of the bead core is positioned from the second row of the metal cords on as counted from the tire radial direction inner end of the bead core outward in the tire radial direction; and the maximum width portion of the bead core is positioned from the second row of the metal cords on as counted from the tir

Abstract: A method which includes obtaining a plurality of images of tires that differ from one another in either one of or both of a tire type and a tire condition, the obtained images being regarded as teacher images; converting the teacher images into a size of a predetermined number of pixels; learning by a convolutional neural network using data of the plurality of converted teacher images as learning images, and setting parameters of the convolutional neural network; obtaining a tire image of a recognition-target tire and converting the obtained tire image into a size identical to that of the teacher images; and inputting the converted tire image of the recognition-target tire to the convolutional neural network and determining either one of or both of the type and the condition of the recognition-target tire.

Abstract: A method which includes obtaining a plurality of images of tires that differ from one another in either one of or both of a tire type and a tire condition, the obtained images being regarded as teacher images; converting the teacher images into a size of a predetermined number of pixels; learning by a convolutional neural network using data of the plurality of converted teacher images as learning images, and setting parameters of the convolutional neural network; obtaining a tire image of a recognition-target tire and converting the obtained tire image into a size identical to that of the teacher images; and inputting the converted tire image of the recognition-target tire to the convolutional neural network and determining either one of or both of the type and the condition of the recognition-target tire.