An image recognition apparatus, configured for supporting creation of a model that recognizes attributes in an image, the apparatus comprising: an image input unit configured to acquire an image (401, 403); a pseudo label generation unit (202, 604) configured to recognize the acquired image based on a plurality of types of image recognition models (51, 52, 53) and output recognition information, and generate pseudo labels (402b, 404b) indicating attributes of the acquired image based on the output recognition information, wherein the attributes of the acquired image comprise one or more objects and/or conditions of the one or more objects in the acquired image; wherein the pseudo label generation unit (202, 604) inputs the acquired image to a plurality of classifiers in which tendencies of the recognition information set as a probability that the acquired image has the attributes are different, the recognition information being output according to characteristic values relating to the attributes of the input image, generates integrated recognition information on the attributes of the acquired image based on the recognition information on the attributes output from the plurality of classifiers, and generates the pseudo labels based on the integrated recognition information, and a new label generation unit configured to generate new labels (402c, 404c) and to calculate recognition accuracies of the pseudo labels for each attribute, characterised in that the new label generation unit compares values of the pseudo labels with values of original labels (402a, 404a) for each attribute, wherein the original labels are preset for the acquired image, and generates the new labels for the attributes of the acquired image based on the calculated recognition accuracies, wherein a recognition accuracy refers to a probability that the value of the original label and the value of the pseudo label relating to a certain attribute are the same, wherein the new label generation unit comprises an attribute threshold value setting unit, wherein the attribute threshold value setting unit is configured to set a threshold parameter for determining, regarding the attributes of the acquired image, whether to use the pseudo labels generated by the pseudo label generation unit as the new labels of the acquired image, wherein the attribute threshold value setting unit is configured to set a first value to a first threshold parameter related to a first attribute having a first recognition accuracy and a second value to a second threshold parameter related to a second attribute having a second recognition accuracy, wherein the first value is greater than the second value when the first recognition accuracy is greater than the second recognition accuracy. an image input unit configured to acquire an image (401, 403); a pseudo label generation unit (202, 604) configured to recognize the acquired image based on a plurality of types of image recognition models (51, 52, 53) and output recognition information, and generate pseudo labels (402b, 404b) indicating attributes of the acquired image based on the output recognition information, wherein the attributes of the acquired image comprise one or more objects and/or conditions of the one or more objects in the acquired image; wherein the pseudo label generation unit (202, 604) inputs the acquired image to a plurality of classifiers in which tendencies of the recognition information set as a probability that the acquired image has the attributes are different, the recognition information being output according to characteristic values relating to the attributes of the input image, generates integrated recognition information on the attributes of the acquired image based on the recognition information on the attributes output from the plurality of classifiers, and generates the pseudo labels based on the integrated recognition information, and a new label generation unit configured to generate new labels (402c, 404c) and to calculate recognition accuracies of the pseudo labels for each attribute, characterised in that the new label generation unit compares values of the pseudo labels with values of original labels (402a, 404a) for each attribute, wherein the original labels are preset for the acquired image, and generates the new labels for the attributes of the acquired image based on the calculated recognition accuracies, wherein a recognition accuracy refers to a probability that the value of the original label and the value of the pseudo label relating to a certain attribute are the same, wherein the new label generation unit comprises an attribute threshold value setting unit, wherein the attribute threshold value setting unit is configured to set a threshold parameter for determining, regarding the attributes of the acquired image, whether to use the pseudo labels generated by the pseudo label generation unit as the new labels of the acquired image, wherein the attribute threshold value setting unit is configured to set a first value to a first threshold parameter related to a first attribute having a first recognition accuracy and a second value to a second threshold parameter related to a second attribute having a second recognition accuracy, wherein the first value is greater than the second value when the first recognition accuracy is greater than the second recognition accuracy.