A system comprising: a camera; and a control device; wherein: the camera is configured to generate an image of a predetermined area of a gaming table that includes a plurality of betting areas; the control device is configured to: use a deep learning convolutional neural network to perform image recognition, that includes extracting features in the image based on color information or a pattern, to identify as processing targets representations in the image of chips stacked in one or more of the betting areas and captured by the camera from a horizontal direction or obliquely from above the chips; and identify, even when the chips stacked in the one or more of the betting areas include one or more chips that are at least partially concealed from view by using image recognition processing of the deep learning convolutional neural network based on the color information or pattern in the image, one or more types, one or more positions, and one or more numbers of the chips including the one or more chips that are at least partially concealed from view, the identification of at least one of (a) the one or more types, (b) the one or more positions, and (c) the one or more numbers being of the identified processing targets in the image; and the convolutional neural network used by the control device is a neural network that performed learning on learning images with labels at targets corresponding to the types of chips represented in the learning images. a camera; and a control device; wherein: the camera is configured to generate an image of a predetermined area of a gaming table that includes a plurality of betting areas; the control device is configured to: use a deep learning convolutional neural network to perform image recognition, that includes extracting features in the image based on color information or a pattern, to identify as processing targets representations in the image of chips stacked in one or more of the betting areas and captured by the camera from a horizontal direction or obliquely from above the chips; and identify, even when the chips stacked in the one or more of the betting areas include one or more chips that are at least partially concealed from view by using image recognition processing of the deep learning convolutional neural network based on the color information or pattern in the image, one or more types, one or more positions, and one or more numbers of the chips including the one or more chips that are at least partially concealed from view, the identification of at least one of (a) the one or more types, (b) the one or more positions, and (c) the one or more numbers being of the identified processing targets in the image; and the convolutional neural network used by the control device is a neural network that performed learning on learning images with labels at targets corresponding to the types of chips represented in the learning images. the camera is configured to generate an image of a predetermined area of a gaming table that includes a plurality of betting areas; the control device is configured to: use a deep learning convolutional neural network to perform image recognition, that includes extracting features in the image based on color information or a pattern, to identify as processing targets representations in the image of chips stacked in one or more of the betting areas and captured by the camera from a horizontal direction or obliquely from above the chips; and identify, even when the chips stacked in the one or more of the betting areas include one or more chips that are at least partially concealed from view by using image recognition processing of the deep learning convolutional neural network based on the color information or pattern in the image, one or more types, one or more positions, and one or more numbers of the chips including the one or more chips that are at least partially concealed from view, the identification of at least one of (a) the one or more types, (b) the one or more positions, and (c) the one or more numbers being of the identified processing targets in the image; and use a deep learning convolutional neural network to perform image recognition, that includes extracting features in the image based on color information or a pattern, to identify as processing targets representations in the image of chips stacked in one or more of the betting areas and captured by the camera from a horizontal direction or obliquely from above the chips; and identify, even when the chips stacked in the one or more of the betting areas include one or more chips that are at least partially concealed from view by using image recognition processing of the deep learning convolutional neural network based on the color information or pattern in the image, one or more types, one or more positions, and one or more numbers of the chips including the one or more chips that are at least partially concealed from view, the identification of at least one of (a) the one or more types, (b) the one or more positions, and (c) the one or more numbers being of the identified processing targets in the image; and the convolutional neural network used by the control device is a neural network that performed learning on learning images with labels at targets corresponding to the types of chips represented in the learning images.