3results about How to "Save labeling time" patented technology

The invention relates to the technical field of artificial intelligence and the technical field of data annotation, and discloses an automatic annotation method, device and equipment and a storage medium, and the method comprises the steps: obtaining a current object image, and obtaining a candidate region outputted by a candidate box generation network based on the current object image; performing feature extraction on the region image corresponding to the candidate region to obtain a current object feature; generating category similarity corresponding to each preset object category; selecting a preset object category with the maximum category similarity as a current object category corresponding to the current object feature; the method comprises the steps of obtaining a polygonal envelope corresponding to an object in a current object image, combining information of the polygonal envelope with a current object category, generating annotation information of the current object image, adding the annotation information to the current object image, and generating an annotated current object image. According to the invention, the marking efficiency of the current object image is improved.

The invention relates to a method for generating a three-dimensional space semantic occupation grid at low cost. The method comprises the following steps: acquiring point cloud data and corresponding obstacle labeling information; according to the marked position of the obstacle, removing the marked point cloud of the obstacle in the point cloud data to obtain background point cloud; segmenting the generated background point cloud by using a ground segmentation algorithm, wherein all points in the background point cloud are divided into ground points and non-ground points; re-integrating the ground point cloud, the non-ground point cloud and the obstacle marking point cloud into a complete point cloud according to the semantics of the respective parts; a occupancy grid is generated for the generated semantic segmentation point cloud using an occupancy grid generation algorithm. According to the method, generation only needs to be carried out through an algorithm on the basis of point cloud obstacle annotation, and compared with point cloud semantic annotation, the cost is reduced by about 10 times on the existing annotation market at present. The technical scheme is simple in design, easy to implement and operate, and beneficial to being popularized and applied to actual scenes.

This application belongs to the field of intelligent input technology, specifically relating to a method, apparatus, and computer-readable storage medium for labeling adjacent key mis-touch information. The method includes: acquiring log information generated by a user inputting information via a keyboard; parsing the log information to obtain target information corresponding to the same input cycle, wherein the target information includes typed information and on-screen information; acquiring the information type corresponding to the typed information and determining target rules based on the information type; performing adjacent key mis-touch analysis on the target information according to the target rules, and labeling adjacent key mis-touch information based on the analysis results, so as to train an adjacent key mis-touch recognition model based on the labeled adjacent key mis-touch information. This application can achieve automated labeling of adjacent key mis-touch information, shortening the information labeling time, reducing mis-labeling caused by manual labeling, accelerating the iteration speed of the adjacent key mis-touch recognition model, and improving the model's accuracy and input accuracy.