Abstract: A task multi-assignment method using a tier data structure of a crowdsourcing-based project, the method being a task assignment method using a tier data structure of a crowdsourcing-based project of a multi-assignment method of duplicately assigning each task to a plurality of n different workers, includes: configuring an assignment tier storage including a queue into which task data corresponding to a task that is not assigned to the worker is enqueued, and one or more jth stacks into which task data corresponding to tasks that are each assigned j times (wherein j is a natural number less than n) are pushed; and assigning a task of the project to a worker (hereinafter, referred to as a target worker) who requests task assignment and requesting the target worker to perform the task, by using the assignment tier storage.

Abstract: Disclosed is an automatic image classification and processing method based on the continuous processing structure of multiple artificial intelligence models. An automatic image classification and processing method based on a continuous processing structure of multiple artificial intelligence models includes receiving image data, generating a first feature extraction value by inputting the image data into a first feature extraction model among feature extraction models, generating a second feature extraction value by inputting the image data into a second feature extraction model among the feature extraction models, and determining a classification value of the image data by inputting the first and second feature extraction values into a classification model.

Abstract: Disclosed are a method and device for managing a project by using data filtering. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.

Abstract: Disclosed are a method and device for managing a project by using a data pointer. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.

Abstract: Disclosed are a method and device for managing a project by using cost payment time point settings. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.

Abstract: Disclosed are a method and device for managing a project by using data merging. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.

Abstract: Provided is a method for automatically updating the unit cost of inspection by using a comparison between inspection time and work time of a crowdsourcing-based project for generating artificial intelligence training data. The method comprises the steps of: determining the unit cost of work and the unit cost of inspection of a new crowdsourcing-based project; opening the new crowdsourcing-based project by applying the unit cost of work and the unit cost of inspection; measuring work time and inspection time for each work datum during a predetermined period; calculating the ratio of the inspection time to the work time for each work datum; calculating the average value of the ratio of the inspection time to the work time calculated for each work datum; and automatically updating the unit cost of inspection by using the unit cost of work and the calculated average value.

Abstract: Provided is a method for increasing or decreasing the number of workers and inspectors in a crowdsourcing-based project for creating artificial intelligence learning data. The method comprises the steps of: opening a new crowdsourcing-based project; setting the ratio of the number of inspectors to the number of standard workers of the project; measuring the number of current workers and the number of current inspectors participating in the project; calculating the ratio of the number of inspectors to the number of current workers of the project by using the measurement result; comparing the ratio of the number of inspectors to the number of current workers with the ratio of the number of inspectors to the number of standard workers; and, according to the comparison result, determining the decrease in the inspectors or the increase in the workers and determining the increase of the inspectors or the decrease of the workers.

Abstract: A worker selection method according to characteristics of a crowdsourcing-based project is provided.

Abstract: Disclosed is a method of adjusting a work unit price according to a work progress speed of a crowdsourcing-based project. The method includes setting a desired work progress speed of the project based on a predetermined work scale of the project and a target work completion period of the project before a project is opened, measuring an actual work progress speed at each predetermined period after the project is opened, and automatically adjusting the work unit price at the respective predetermined period by comparing the desired work progress speed with the actual work progress speed.

Abstract: Provided is a method, device, and program for sampling a frame image of an object to be learned in a video for artificial intelligence video learning, and an image learning method thereof. The method includes receiving a raw video for the AI image learning, extracting a predetermined number of frame images from the received raw, detecting learning target objects in each of the frame images, removing a background other than the learning target objects from each of the frame images, measuring a movement amount of each of the detected learning target objects in a n-th frame image, from which the background is removed, and selecting the n-th frame image as the learning target frame image, by comparing a result of measuring the movement amount of each of the detected one or more learning target objects in the n-th frame image with a predetermined reference.

Abstract: A worker selection method according to characteristics of a crowdsourcing-based project is provided.

Abstract: Provided is a method, device, and program for sampling a frame image of an object to be learned in a video for artificial intelligence video learning, and an image learning method thereof. The method includes receiving a raw video for the AI image learning, extracting a predetermined number of frame images from the received raw, detecting learning target objects in each of the frame images, removing a background other than the learning target objects from each of the frame images, measuring a movement amount of each of the detected learning target objects in a n-th frame image, from which the background is removed, and selecting the n-th frame image as the learning target frame image, by comparing a result of measuring the movement amount of each of the detected one or more learning target objects in the n-th frame image with a predetermined reference.