Abstract: A processor-implemented method with visual code processing includes generating a first image by capturing a first visual code, using an always on (AO) sensor module of an electronic device, detecting a first code image included in the first image and corresponding to the first visual code, using the AO sensor module, performing a first type decoding on the first code image, using the AO sensor module, waking up an application processor (AP) of the electronic device from a low-power state, based on a first decoding result of the first type decoding, and executing a first application of the electronic device corresponding to the first visual code, using the AP.

Abstract: A method of operating an electronic device includes: inputting a multi-frame image to a first image segmentation model that infers therefrom preliminary segmentation probability maps of the respective frames included in the multi-frame image; forming the preliminary segmentation probability maps into respective final segmentation probability maps by aligning the preliminary segmentation probability maps into a same three-dimensional space according to differences in poses of the respective frames, each pose including an angle and position of its corresponding frame; and obtaining a final image segmentation result for the multi-frame image based on inputting the obtained final segmentation probability maps to a second image segmentation model.

Abstract: A processor-implemented method including, based on a first shape of a first tensor and a second shape of a second tensor used in an operation with the first tensor, determining a broadcasting type related to an extension of the first shape and the second shape, determining respective first shape offsets for each dimension of the first shape and respective second shape offsets for each dimension of the second shape based on the broadcasting type, determining respective first tensor offsets for each dimension of the first tensor and respective second tensor offsets for each dimension of the second tensor based on the broadcasting type, the respective first shape offsets for each dimension of the first shape, and the respective second shape offsets for each dimension of the second shape, determining a first offset of a first element included in the first tensor and a second offset of a second element included in the second tensor based on the respective first tensor offsets and the respective second tensor offse

Abstract: The present disclosure relates to a fingerprint identification method, device, an electronic apparatus and a storage medium. The fingerprint identification method includes: capturing a fingerprint by a fingerprint sensor, identifying matching pairs of minutiae between the captured fingerprint and a reference fingerprint; calculating a first matching result based on the minutia matching pairs; identifying minutia surrounding features for each minutia of the captured fingerprint in the minutia matching pairs; determining, for each minutia in the minutia matching pairs, whether the minutia surrounding features of the captured fingerprint match with minutia surrounding features of the reference fingerprint; calculating a second matching result based on the determination; and generating an identification result based on the first matching result and the second matching result.

Abstract: A method of estimating a state includes: predicting current state prediction data of a target object by using previous state estimation data of a previous image frame of an image sequence in which the target object is represented, the previous image frame previous to a current image frame; acquiring current target detection data of the target object for the current image frame of the image sequence; and determining current state estimation data of the target object of the current image frame by updating the current state prediction data by using the current target detection data and by using a detection reliability of the current target detection data.

Abstract: An apparatus and method for quantizing a transformer-based target tracking model are provided. The method includes obtaining a transformer-based target tracking model including a template branch, a search branch, a stitching module, and a first transformer module, generating an optimized target tracking model by removing the stitching module from the transformer-based target tracking model and dividing the first transformer module into a second transformer module and a third transformer module, and generating a quantization model corresponding to the optimized target tracking model by quantizing the divided second transformer module independently of quantizing the divided third transformer module.

Abstract: Various example embodiments are directed to a fingerprint authentication method and a fingerprint authentication device. The fingerprint authentication method includes acquiring target fingerprint data of a user using at least one fingerprint sensor, determining a preliminary authentication result of the target fingerprint data based on at least one historical fingerprint data stored in memory, performing a matching check on the preliminary authentication result, and determining a final authentication result of the target fingerprint data based on results of the matching check.

Abstract: A processor-implemented method with visual code processing includes generating a first image by capturing a first visual code, using an always on (AO) sensor module of an electronic device, detecting a first code image included in the first image and corresponding to the first visual code, using the AO sensor module, performing a first type decoding on the first code image, using the AO sensor module, waking up an application processor (AP) of the electronic device from a low-power state, based on a first decoding result of the first type decoding, and executing a first application of the electronic device corresponding to the first visual code, using the AP.

Abstract: The present disclosure relates to a fingerprint identification method, device, an electronic apparatus and a storage medium. The fingerprint identification method includes: capturing a fingerprint by a fingerprint sensor, identifying matching pairs of minutiae between the captured fingerprint and a reference fingerprint; calculating a first matching result based on the minutia matching pairs; identifying minutia surrounding features for each minutia of the captured fingerprint in the minutia matching pairs; determining, for each minutia in the minutia matching pairs, whether the minutia surrounding features of the captured fingerprint match with minutia surrounding features of the reference fingerprint; calculating a second matching result based on the determination; and generating an identification result based on the first matching result and the second matching result.

Abstract: Various example embodiments are directed to a fingerprint authentication method and a fingerprint authentication device. The fingerprint authentication method includes acquiring target fingerprint data of a user using at least one fingerprint sensor, determining a preliminary authentication result of the target fingerprint data based on at least one historical fingerprint data stored in memory, performing a matching check on the preliminary authentication result, and determining a final authentication result of the target fingerprint data based on results of the matching check.