Abstract: The present disclosure provides an arctigenin liquid nano-preparation and a preparation method thereof, and relates to the technical field of pharmaceutical preparation. In the present disclosure, arctigenin is prepared into a liquid nano-preparation, having advantages of distribution of a droplet diameter on nanoscale, significantly increased specific surface area, rapid absorption, and high bioavailability. Meanwhile, nano-preparation entered the body can be captured by wandering leucocytes, and a medicament is delivered to inflammatory lesions through chemiotaxis, thereby conferring a targeted drug delivery feature on the arctigenin and making a therapy more targeted. Moreover, in the present disclosure, the arctigenin is dissolved in an oil phase, and the oil phase is dissolved in water by emulsification to further make the arctigenin dissolve in the water and increase water solubility of the arctigenin.

Abstract: A gaze estimation method and apparatus is disclosed. The gaze estimation method includes obtaining an image including an eye region of a user, extracting, from the obtained image, a first feature of data, obtaining a second feature of data used for calibration of a neural network model, and estimating a gaze of the user using the first feature and the second feature.

Abstract: A gaze estimation method includes receiving, by a processor, input data including a current image and a previous image each including a face of a user, determining, by the processor, a gaze mode indicating a relative movement between the user and a camera that captured the current image and the previous image based on the input data, and estimating, by the processor, a gaze of the user based on the determined gaze mode, wherein the determined gaze mode is one of a plurality of gaze modes comprising a stationary mode and a motion mode.

Abstract: A gaze tracking method and apparatus, and a gaze tracking neural network training method and apparatus are provided. The gaze tracking apparatus includes one or more processors and a memory, and the one or more processors obtain output position information from an input face image of a user using a neural network model, determines a position adjustment parameter for the user, and predicts gaze position information of the user by adjusting the output position information based on the position adjustment parameter.

Abstract: A gaze estimation method and apparatus is disclosed. The gaze estimation method includes obtaining an image including an eye region of a user, extracting, from the obtained image, a first feature of data, obtaining a second feature of data used for calibration of a neural network model, and estimating a gaze of the user using the first feature and the second feature.

Abstract: A gaze estimation method and apparatus is disclosed. The gaze estimation method includes obtaining an image including an eye region of a user, extracting, from the obtained image, a first feature of data, obtaining a second feature of data used for calibration of a neural network model, and estimating a gaze of the user using the first feature and the second feature.

Abstract: An image processing method and apparatus using a neural network are provided. The image processing method includes generating a plurality of augmented features by augmenting an input feature, and generating a prediction result based on the plurality of augmented features.

Abstract: A gaze tracking method and apparatus, and a gaze tracking neural network training method and apparatus are provided. The gaze tracking apparatus includes one or more processors and a memory, and the one or more processors obtain output position information from an input face image of a user using a neural network model, determines a position adjustment parameter for the user, and predicts gaze position information of the user by adjusting the output position information based on the position adjustment parameter.

Abstract: A gaze estimation method and apparatus is disclosed. The gaze estimation method includes obtaining an image including an eye region of a user, extracting, from the obtained image, a first feature of data, obtaining a second feature of data used for calibration of a neural network model, and estimating a gaze of the user using the first feature and the second feature.

Abstract: A gaze estimation method includes receiving, by a processor, input data including a current image and a previous image each including a face of a user, determining, by the processor, a gaze mode indicating a relative movement between the user and a camera that captured the current image and the previous image based on the input data, and estimating, by the processor, a gaze of the user based on the determined gaze mode, wherein the determined gaze mode is one of a plurality of gaze modes comprising a stationary mode and a motion mode.

Abstract: A user trigger intent determining method and apparatus is disclosed. The user trigger intent determining apparatus may obtain a first face image, obtain a second face image after a visual stimuli object is displayed, and determine a final gaze location by correcting a first gaze location estimated from the first face image based on a second gaze location estimated from the second face image.

Abstract: A method of determining the length of a cable coupled to a transceiver of a network device includes transmitting a first series of pulses of a first pulse width onto a cable, receiving reflections of the first series of pulses, transmitting a second series of pulses of a second pulse width onto the cable, and receiving reflections of the second series of pulses. The second pulse width is wider than the first pulse width. It is determined whether the reflections of the first series of pulses satisfy a criterion. The length of the cable is calculated using either the reflections of the first series of pulses or the reflections of the second series of pulses, based at least in part on whether the reflections of the first series of pulses satisfy the criterion.

Abstract: A method of determining the length of a cable coupled to a transceiver of a network device includes transmitting a first series of pulses of a first pulse width onto a cable, receiving reflections of the first series of pulses, transmitting a second series of pulses of a second pulse width onto the cable, and receiving reflections of the second series of pulses. The second pulse width is wider than the first pulse width. It is determined whether the reflections of the first series of pulses satisfy a criterion. The length of the cable is calculated using either the reflections of the first series of pulses or the reflections of the second series of pulses, based at least in part on whether the reflections of the first series of pulses satisfy the criterion.