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    Fully human antibody specifically inhibiting Connexin 26
    81.
    发明授权
    Fully human antibody specifically inhibiting Connexin 26 有权

    公开(公告)号：US11345746B2

    公开(公告)日：2022-05-31

    申请号：US15781463

    申请日：2016-12-14

    Applicant: SHANGHAITECH UNIVERSITY

    Inventor： Zhihu Qu ,  Guang Yang ,  Fabio Mammano ,  Francesco Zonta

    IPC: C07K16/18 ,  A61K39/395 ,  A61K39/00

    Abstract: The present invention provides a fully human antibody specifically inhibiting Connexin 26, characterized in that it is a recombinant immunoglobulin having the structure of scFv-Fc, wherein scFv refers to a single-chain antibody comprising a heavy chain variable region and a light chain variable region, the amino acid sequence of the heavy chain variable region is SEQ ID NO: 1, the amino acid sequence of the light chain variable region is SEQ ID NO: 2, and Fc refers to constant region. The present invention uses the first 41-56 amino acid sequence of extracellular region of Connexin26 as an antigen, the sequence thereof is KEVWGDEQADFVCNTL. Through the biochemical analysis and immunofluorescence identification of the antibody obtained by single-chain antibody phage display library and screening technology, it was confirmed that the antibody provided by the present invention could specifically recognize Connexin 26 and inhibit its hemichannel activity. Animal experiments show that this antibody significantly inhibits the hemichannel activity of mouse cochlear tissue sections. Therefore, the antibody can be used in the treatment of Connexin mutation associated diseases.

    ADAPTIVE STEREO MATCHING OPTIMIZATION METHOD AND APPARATUS, DEVICE AND STORAGE MEDIUM
    82.
    发明申请
    ADAPTIVE STEREO MATCHING OPTIMIZATION METHOD AND APPARATUS, DEVICE AND STORAGE MEDIUM 有权

    公开(公告)号：US20210390725A1

    公开(公告)日：2021-12-16

    申请号：US17286488

    申请日：2019-09-20

    Applicant: ShanghaiTech University

    Inventor： Fupeng CHEN ,  Heng YU ,  Yajun HA

    IPC: G06T7/593 ,  G06F17/12

    Abstract: The present disclosure provides an adaptive stereo matching optimization method, apparatus, and device, and a storage medium. The method includes: acquiring images of at least two perspectives of the same target scene, accordingly obtaining, through calculation, disparity value ranges corresponding to pixels in the target scene; and obtaining optimized depth value ranges by adjusting the disparity value ranges of the pixels in the target scene in real time through an adaptive stereo matching model; adjusting an execution cycle in the adaptive stereo matching model in real time through a DVFS algorithm according to a resource constraint condition of the processing system; and/or training on a plurality of scene image data sets through a convolutional neural network, so that the specific function parameters in the adaptive stereo matching model are correspondingly adjusted in real time according to the acquired different scene images.

    Low-power SRAM memory cell and application structure thereof
    84.
    发明授权
    Low-power SRAM memory cell and application structure thereof 有权

    公开(公告)号：US11100979B1

    公开(公告)日：2021-08-24

    申请号：US17051783

    申请日：2020-06-17

    Applicant: SHANGHAITECH UNIVERSITY

    Inventor： Yuqi Wang ,  Yajun Ha

    IPC: G11C11/412 ,  H01L27/11 ,  G11C11/419

    Abstract: A low-power SRAM memory cell includes five word lines and four bit lines. The five word lines are a first word line, a second word line, a third word line, a fourth word line and a fifth word line. The four bit lines are a first bit line, a second bit line, a third bit line, and a fourth bit line. During the operation process of calculating a binary 10×11, the first word line is 1, the second word line is 0, the third word line is 0, the fourth word line is 1, the high bit stored in the bit cell is 1, and the low bit is 1. The voltage value of the fifth word line is 0.73 volt. At this time, the first bit line, the second bit line, and the third bit line do not discharge, while the fourth bit line discharges.

    LOW-POWER SRAM MEMORY CELL AND APPLICATION STRUCTURE THEREOF
    85.
    发明申请
    LOW-POWER SRAM MEMORY CELL AND APPLICATION STRUCTURE THEREOF 有权

    公开(公告)号：US20210249069A1

    公开(公告)日：2021-08-12

    申请号：US17051783

    申请日：2020-06-17

    Applicant: SHANGHAITECH UNIVERSITY

    Inventor： Yuqi WANG ,  Yajun HA

    IPC: G11C11/412 ,  G11C11/419 ,  H01L27/11

    Abstract: A low-power SRAM memory cell includes five word lines and four bit lines. The five word lines are a first word line, a second word line, a third word line, a fourth word line and a fifth word line. The four bit lines are a first bit line, a second bit line, a third bit line, and a fourth bit line. During the operation process of calculating a binary 10×11, the first word line is 1, the second word line is 0, the third word line is 0, the fourth word line is 1, the high bit stored in the bit cell is 1, and the low bit is 1. The voltage value of the fifth word line is 0.73 volt. At this time, the first bit line, the second bit line, and the third bit line do not discharge, while the fourth bit line discharges.

    SYSTEM AND METHOD FOR EXTRACTING PLANAR SURFACE FROM DEPTH IMAGE
    86.
    发明申请
    SYSTEM AND METHOD FOR EXTRACTING PLANAR SURFACE FROM DEPTH IMAGE 有权

    公开(公告)号：US20210241462A1

    公开(公告)日：2021-08-05

    申请号：US17219555

    申请日：2021-03-31

    Applicant: SHANGHAITECH UNIVERSITY

    Inventor： Ziran XING ,  Zhiru SHI ,  Yi MA ,  Jingyi YU

    IPC: G06T7/11 ,  G06T7/50 ,  G06T7/187 ,  G06T7/162

    Abstract: According to some embodiments, an imaging processing method for extracting a plurality of planar surfaces from a depth map includes computing a depth change indication map (DCI) from a depth map in accordance with a smoothness threshold. The imaging processing method further includes recursively extracting a plurality of planar region from the depth map, wherein the size of each planar region is dynamically adjusted according to the DCI. The imaging processing method further includes clustering the extracted planar regions into a plurality of groups in accordance with a distance function; and growing each group to generate pixel-wise segmentation results and inlier points statistics simultaneously.

    LIGHT FIELD BASED REFLECTION REMOVAL
    87.
    发明申请
    LIGHT FIELD BASED REFLECTION REMOVAL 有权

    公开(公告)号：US20210082096A1

    公开(公告)日：2021-03-18

    申请号：US17074123

    申请日：2020-10-19

    Applicant: SHANGHAITECH UNIVERSITY

    Inventor： Minye WU ,  Zhiru SHI ,  Jingyi YU

    IPC: G06T5/50 ,  G06T7/557 ,  G06T7/593

    Abstract: A method of processing light field images for separating a transmitted layer from a reflection layer. The method comprises capturing a plurality of views at a plurality of viewpoints with different polarization angles; obtaining an initial disparity estimation for a first view using SIFT-flow, and warping the first view to a reference view; optimizing an objective function comprising a transmitted layer and a secondary layer using an Augmented Lagrange Multiplier (ALM) with Alternating Direction Minimizing (ADM) strategy; updating the disparity estimation for the first view; repeating the steps of optimizing the objective function and updating the disparity estimation until the change in the objective function between two consecutive iterations is below a threshold; and separating the transmitted layer and the secondary layer using the disparity estimation for the first view.

    FAST AND DETERMINISTIC ALGORITHM FOR CONSENSUS SET MAXIMIZATION
    88.
    发明申请
    FAST AND DETERMINISTIC ALGORITHM FOR CONSENSUS SET MAXIMIZATION 有权

    公开(公告)号：US20210073443A1

    公开(公告)日：2021-03-11

    申请号：US17099445

    申请日：2020-11-16

    Applicant: SHANGHAITECH UNIVERSITY

    Inventor： Zhiru Shi ,  Ziran Xing

    IPC: G06F30/20 ,  G06F17/16

    Abstract: A method for approximately solving a consensus set maximization (“CSM”) problem for a dataset is disclosed. The method comprises relaxing a maximum fitting residual constraint in the CSM problem to an average error bounded constraint; defining a plurality of decision problems related to the relaxed CSM problem; solving each decision problem by defining an optimization problem; and selecting a consensus size for the CSM problem based on solutions to the decision problems.

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