Abstract: A PD-L1 antigen binding protein and an application thereof. The antigen binding protein has one or more of the following properties: binding to a PD-L1 protein at an EC50 value of 0.07 ?g/ml or above; blocking binding between the PD-L1 protein and a PD-1 protein; promoting the activation of a T cell; and inhibiting the volume increase of the in vivo tumor. An application of the antigen binding protein in the preparation of a drug for treating tumor.

Abstract: The present invention provides an image processing method, wherein the image processing method includes the steps of: receiving an image signal, wherein the image signal comprises a frame; performing a motion estimation operation on a plurality of blocks within the frame to generate a plurality of first motion vectors, respectively; scaling down the frame to generate a scaled-down frame; performing the motion estimation operation on a specific block within the scaled-down frame to generate a second motion vector corresponding to the specific block; and determining a plurality of final motion vectors of the plurality of blocks of the frame according to the plurality of first motion vectors and the second motion vector.

Abstract: A video processing method includes dividing a current frame into a plurality of blocks, generating a motion vector of each block of the plurality of blocks of the current frame according to the each block of the current frame and a corresponding block of a previous frame, generating a global motion vector according to a plurality of motion vectors of the current frame, generating a sum of absolute differences of pixels of each block of the current frame according to the global motion vector, generating a region with a set of blocks of the current frame, matching a distribution of the sum of absolute differences of pixels of the region with a plurality of models, identifying a best matching model, and labeling each block in the region in the current frame with a label of either a foreground block or a background block according to the best matching model.

Abstract: A video processing method includes dividing a current frame into a plurality of blocks, generating a motion vector of each block of the plurality of blocks of the current frame according to the each block of the current frame and a corresponding block of a previous frame, generating a global motion vector according to a plurality of motion vectors of the current frame, generating a sum of absolute differences of pixels of each block of the current frame according to the global motion vector, generating a region with a set of blocks of the current frame, matching a distribution of the sum of absolute differences of pixels of the region with a plurality of models, identifying a best matching model, and labeling each block in the region in the current frame with a label of either a foreground block or a background block according to the best matching model.

Abstract: An apparatus and a method for motion estimation of isolated objects are provided. The apparatus includes a dividing circuit, a flag circuit, an analyzing circuit, a calculating circuit and a determination circuit. The dividing circuit divides each of a first image and a second image into a plurality of blocks. The flag circuit adds a flag to each block within the blocks having image information different from background information. The analyzing circuit analyzes continuity of the flag to find a target isolated object having a size less than or equal to a predetermined size. The calculating circuit obtains an initial motion vector of the target isolated object according to locations of the target isolated object in the first image and the second image. The determination circuit determines whether the initial motion vector is correct according to a sum of absolute differences corresponding to the initial motion vector.

Abstract: An apparatus and a method for motion estimation of isolated objects are provided. The apparatus includes a dividing circuit, a flag circuit, an analyzing circuit, a calculating circuit and a determination circuit. The dividing circuit divides each of a first image and a second image into a plurality of blocks. The flag circuit adds a flag to each block within the blocks having image information different from background information. The analyzing circuit analyzes continuity of the flag to find a target isolated object having a size less than or equal to a predetermined size. The calculating circuit obtains an initial motion vector of the target isolated object according to locations of the target isolated object in the first image and the second image. The determination circuit determines whether the initial motion vector is correct according to a sum of absolute differences corresponding to the initial motion vector.

Abstract: Embodiments of the invention can predict the ground location and intensity of storm cells for a future time using radar reflectivity data. In some embodiments, a Sinc approximation of the general flow equation can be solved to predict the ground location and intensity of a storm cell. In some embodiments, to solve the Sinc approximation the velocity of a storm cell can be estimated using various techniques including solving the flow equation in the frequency domain. The results can provide efficient prediction of storm cell position in nowcasting applications.

Abstract: Embodiments of the invention can predict the ground location and intensity of storm cells for a future time using radar reflectivity data. In some embodiments, a Sinc approximation of the general flow equation can be solved to predict the ground location and intensity of a storm cell. In some embodiments, to solve the Sinc approximation the velocity of a storm cell can be estimated using various techniques including solving the flow equation in the frequency domain. The results can provide efficient prediction of storm cell position in nowcasting applications.

Abstract: Systems and methods are provided for adaptively estimating the specific differential phase (Kdp) from dual-polarization radar data in the complex domain. Some embodiments adapt for wrapped differential propagation phases by estimating the specific differential phase in the complex domain. Some embodiments adapt for measurement fluctuations and/or spatial scale in making such estimations. Some embodiments also provide for determining the presence of storms cells using the dispersion of the differential propagation phase shift over a subset of bins.

Abstract: Methods and systems for estimating atmospheric conditions are disclosed according to embodiments of the invention. In one embodiment, a method may include receiving reflective atmospheric data and solving a flow equation for motion coefficients using the reflective atmospheric data. Future atmospheric conditions can be estimated using the motion coefficients and the reflective atmospheric data. In another embodiment of the invention, the flow equation is solved in the frequency domain. Various linear regression tools may be used to solve for the coefficients. In another embodiment of the system, a radar system is disclosed that predicts future atmospheric conditions by solving the spectral flow equation.

Abstract: Systems and methods are provided for adaptively estimating the specific differential phase (Kdp) from dual-polarization radar data in the complex domain. Some embodiments adapt for wrapped differential propagation phases by estimating the specific differential phase in the complex domain. Some embodiments adapt for measurement fluctuations and/or spatial scale in making such estimations. Some embodiments also provide for determining the presence of storms cells using the dispersion of the differential propagation phase shift over a subset of bins.

Abstract: Methods and systems for estimating atmospheric conditions are disclosed according to embodiments of the invention. In one embodiment, a method may include receiving reflective atmospheric data and solving a flow equation for motion coefficients using the reflective atmospheric data. Future atmospheric conditions can be estimated using the motion coefficients and the reflective atmospheric data. In another embodiment of the invention, the flow equation is solved in the frequency domain. Various linear regression tools may be used to solve for the coefficients. In another embodiment of the system, a radar system is disclosed that predicts future atmospheric conditions by solving the spectral flow equation.