公开(公告)号：US20180082064A1

公开(公告)日：2018-03-22

申请号：US15645767

申请日：2017-07-10

Applicant: SICHUAN UNIVERSITY ,  BEIJING TONGTECH CO., LTD.

Inventor： Junfeng WANG ,  Baoxin XU ,  Dong LIU ,  Fan LI ,  Xiaosong ZHANG

IPC: G06F21/56 ,  G06N99/00

CPC classification number: G06F21/566 ,  G06F21/563 ,  G06F2221/033 ,  G06N5/003 ,  G06N7/005 ,  G06N20/00

Abstract: A method of detecting malware in Linux platform through the following steps: use objdump-D command to disassemble ELF format benign software and malware samples to generate assembly files; traverse the generated assembly files one by one, read the ELF files' code segment and meanwhile identify whether the code segment contains main( ) function; analyze the code segment read. Divide assembly code into different basic blocks. Each basic block is marked by its lowest address. Add control flow graph's vertex to the adjacency linked list; establish the relation between basic blocks, add control flow graph's edges to the adjacency linked list and generate a basic control flow graph; extract control flow graph's features and write them into ARFF files; take ARFF files as the data set of a machine learning tool named weka to carry out data mining and construct classifier; classify the ELF samples to be tested by using the classifier.

公开(公告)号：US20170337686A1

公开(公告)日：2017-11-23

申请号：US15598656

申请日：2017-05-18

Applicant: SICHUAN UNIVERSITY

Inventor： Junfeng WANG ,  Lin GAO ,  Fan LI ,  Yulin JI ,  Zongan LIANG

IPC: G06T7/00 ,  G06T7/11

CPC classification number: G06T7/0012 ,  G06T5/10 ,  G06T5/20 ,  G06T7/11 ,  G06T7/136 ,  G06T7/168 ,  G06T7/262 ,  G06T2207/10116 ,  G06T2207/20016 ,  G06T2207/30008 ,  G06T2207/30061

Abstract: A X-ray chest image rib suppression method based on Poisson model. It conducts contourlet transformation on the image and utilizes transformation coefficient correlation between different scales to conduct texture enhancement on the image; it designs strip-type detection filter in accordance with the Hessian matrix eigenvalue to the image and detects the area where the rib locates in; it combines enhanced texture and rib area information, establishes and solves rib suppression Poisson model, realizing the rib suppression in the image. Anisortropy and contourlet transformation multi-direction feature is utilized, scale and coefficients direction information are combined and distinction degree between texture and noise improves, enhancing texture while restraining noise; it realizes ribs suppression through solving the Poisson model, which does not need to conduct accurate segmentation on the rib, prevents unnatural transition problem of edges resulted from explicit ribs suppression and effectively suppress the ribs, improving observation effect of X-ray chest image.

公开(公告)号：US20180130202A1

公开(公告)日：2018-05-10

申请号：US15598628

申请日：2017-05-18

Applicant: SICHUAN UNIVERSITY

Inventor： Junfeng WANG ,  Peng TANG ,  Fan LI ,  Yihua Du ,  Yulin JI ,  Zongan LIANG

IPC: G06T7/00 ,  G06T7/13 ,  A61B6/00

CPC classification number: G06T7/0012 ,  A61B6/50 ,  A61B6/5211 ,  A61B6/5217 ,  G06T7/13 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30061

Abstract: A DR radiography lung contour extraction method based on fully convolutional network, which includes the steps: Establish the fully convolutional network structure of lung contour segmentation; Conduct off-line training on the weighting parameters of the fully convolutional network; Read DR image and weighting parameters of the fully convolutional network; Input DR image into fully convolutional network and output segmentation results of image through network terminal with network layer-by-layer feedforward. Establish lung contour in accordance with segmentation results.