4results about How to "Improve image recognition accuracy" patented technology

This application relates to an image segmentation method, apparatus, device, and storage medium, specifically in the field of image detection technology. The method includes: acquiring sample image data; extracting features from the sample image data using a downsampling module of an object detection model to obtain a target sample feature map; upsampling the target sample feature map using an upsampling module in the object detection model to obtain at least two levels of upsampled feature maps; obtaining a first loss function value based on the top-level upsampled feature map and sample annotations; performing channel compression on the at least two levels of upsampled feature maps to obtain at least two layers of compressed feature maps; obtaining a second loss function value based on the at least two layers of compressed feature maps and sample annotations; and training the object detection model using the first and second loss function values ​​to obtain a trained object detection model. Based on the above scheme, the image recognition accuracy of the object detection model is improved.

This invention discloses a knowledge distillation method and system for image recognition uncertainty. The method involves collecting labeled training image samples; selecting a first neural network model and training it using the training image samples to obtain a trained first neural network model; inputting training sample images to obtain the intermediate layer sample feature representations and output soft label information of the first neural network model; selecting a second neural network model and processing the training image samples to obtain intermediate layer sample feature representations; performing uncertainty modeling between the intermediate layer sample feature representations of the first neural network model and the first neural network model to obtain a first loss function; using the soft label information output by the first neural network model and the training image samples, combined with the first loss function, updating the parameters of the second neural network model to obtain a trained second neural network model; and simultaneously using the second neural network model of this invention to perform image recognition processing on the image to be processed, thereby improving the accuracy of image recognition.

The invention discloses an object abnormal behavior identification method, a storage medium and a processor. The method comprises the following steps: identifying a target object from the image content of image data; a target abnormal behavior rule corresponding to the target object is determined, and the target abnormal behavior rule is used for representing a target abnormal behavior of the target object; identifying the image data by using a target abnormal behavior rule to obtain an identification result, the identification result being used for representing a matching degree between a target abnormal behavior and an actual execution behavior of the target object; in response to the identification result, representing that the matching degree meets a degree threshold, verifying the image data to obtain a verification result, the verification result being used for representing the possibility degree that the actual execution behavior is the target abnormal behavior; and based on the identification result and the verification result, determining a target confidence degree corresponding to the actual execution behavior. The technical problem of low image recognition accuracy is solved.

The utility model discloses a kind of personnel safety detection devices of inclined shaft track transportation system, including mounting seat, safety detection mechanism and positioning bracelet;Mounting seat is installed in track one side after, top surface is provided with support rod;Safety detection mechanism includes camera and receiver, camera and receiver are all detachably installed at different height of support rod by limiting mechanism;Positioning bracelet is worn on the wrist of transport personnel after, signal transmission is given receiver, the distance between transport personnel and track is obtained under the cooperation of processor.The utility model is compared with prior art in that: positioning bracelet+receiver+processor linkage, realize the real-time positioning and distance calculation of transport personnel, when personnel enters dangerous area, it can automatically early warning or linkage control system stops running;Limiting mechanism supports the quick installation and disassembly of detection equipment, is convenient for maintenance and replacement, improve equipment availability.