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91. 发明申请

US20190026897A1 BRAIN TUMOR AUTOMATIC SEGMENTATION METHOD BY MEANS OF FUSION OF FULL CONVOLUTIONAL NEURAL NETWORK AND CONDITIONAL RANDOM FIELD 审中-公开
公开(公告)号：US20190026897A1
公开(公告)日：2019-01-24
申请号：US16070882
申请日：2016-11-07
申请人： Institute of Automation, Chinese Academy of Sciences
发明人： Yihong WU , Xiaomei ZHAO
IPC分类号： G06T7/11 , G06T5/40 , G06T11/00
CPC分类号： G06T7/11 , G06T5/009 , G06T5/40 , G06T7/136 , G06T7/143 , G06T11/005 , G06T2207/10088 , G06T2207/20024 , G06T2207/20081 , G06T2207/30016 , G06T2207/30096
摘要： A method for automatic segmentation of brain tumors merging full convolution neural networks with conditional random fields. The present application intends to address the issue that presently the technology of deep learning is unable to ensure the continuity of the segmentation result in shape and in space when segmenting brain tumors. For this purpose, the present application includes the following steps: step 1, processing a magnetic resonance image comprising brain tumors by utilizing a method for non-uniformity bias correction and brightness regularization, to generate a second magnetic resonance image; step 2, performing brain tumor segmentation for said second magnetic resonance image by utilizing a neural network merging a full convolutional neural network with a conditional random field, and outputting a result of brain tumor segmentation. The present method may execute brain tumor segmentation end-to-end and slice by slice during testing, which has relatively high computation efficiency.

92. 发明申请

US20190012520A1 Method for Microscopic Image Acquisition Based on Sequential Section 审中-公开
公开(公告)号：US20190012520A1
公开(公告)日：2019-01-10
申请号：US16066879
申请日：2016-11-07
申请人： Institute of Automation, Chinese Academy of Sciences
发明人： Guoqing LI , Hongtu MA , Hua HAN , Lixin WEI
IPC分类号： G06K9/00 , G06K9/62 , G06K9/68
CPC分类号： G06K9/00134 , G06K9/0014 , G06K9/00147 , G06K9/6206 , G06K9/6211 , G06K9/6257 , G06K9/6262 , G06K9/6269 , G06K9/6857
摘要： A method for microscopic image acquisition based on a sequential slice. The method includes; acquiring a sample of the sequential slice and a navigation image thereof; identifying and labeling the sample of the sequential slice in the navigation image by utilizing methods of image processing and machine learning; placing the sample of the sequential slice in a microscope, establishing a coordinate transformation matrix for a navigation image-microscope actual sampling space coordinate, and navigating and locating a random pixel point in the navigation image to a center of the microscope's visual field; locating the sample of the sequential slice under a low resolution visual field, binding a sample acquisition parameter; based on the binding of the sample acquisition parameter, recording a relationship of relative of locations between a center point of a high resolution acquisition region and a center point after being matched with a sample template.

93. 发明申请

US20180288084A1 METHOD AND DEVICE FOR AUTOMATICALLY ESTABLISHING INTRUSION DETECTION MODEL BASED ON INDUSTRIAL CONTROL NETWORK 审中-公开
公开(公告)号：US20180288084A1
公开(公告)日：2018-10-04
申请号：US15572643
申请日：2017-04-17
申请人： SHENYANG INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES
发明人： Wenli SHANG , Jianming ZHAO , Ming WAN , Xianda LIU , Long YIN , Peng ZENG , Haibin YU
IPC分类号： H04L29/06 , G06K9/62
摘要： The present application discloses a method for automatically establishing an intrusion detection model based on an industrial control network, including: judging whether a first intrusion detection model meets preset detection requirements, and extracting communication behavior traffic data in real time if not; setting a training data set and a test date set according to the communication behavior traffic data; establishing an initial intrusion detection model according to the training data set; and testing the initial intrusion detection model using the test date set, and establishing a second intrusion detection model meeting the preset detection requirements according to the test result. The second intrusion detection model has high detection accuracy, thereby increasing intrusion detection rate of abnormal behavior and reducing false positive rate and false negative rate.

94. 发明申请

US20180166125A1 Memory Cell of Static Random Access Memory Based on Resistance and Capacitance Hardening 审中-公开
公开(公告)号：US20180166125A1
公开(公告)日：2018-06-14
申请号：US15551008
申请日：2015-03-27
申请人： Institute of Automation Chinese Academy of Sciences
发明人： Jingqiu Wang , Liang Chen , Li LIU
IPC分类号： G11C11/417 , G11C11/412 , H01L27/11
CPC分类号： G11C11/417 , G11C11/4125 , H01L27/1104
摘要： The present invention provides a memory cell of static random access memory based on resistance-capacitance reinforcement, which comprises a latch circuit and a bit selection circuit, the latch circuit consists of two PMOS transistors P1 and P2, two NMOS transistors N1 and N2, a first resistance-capacitance network and a second resistance-capacitance network; the bit selection circuit consists of NMOS transistors N5 and N6; the latch circuit forms four storage nodes X1, X1B, X2, X2B, among which a coupling capacitor C is provided between a pair of complementary data storage nodes. Compared to the conventional memory cell of 6T structure, a resistance-capacitance network and a coupling capacitor are added, so that without changing the original read operation circuit and without obviously increasing complexity, the memory cell is prevented from having single event upset merely at a cost of increasing a small amount of area, thus ensuring correctness of data.

95. 发明授权

US09996764B2 Image matching method based on cascaded binary encoding 有权
公开(公告)号：US09996764B2
公开(公告)日：2018-06-12
申请号：US15306983
申请日：2014-04-29
申请人： Institute of Automation Chinese Academy of Sciences
发明人： Jian Cheng , Cong Leng , Jiaxiang Wu , Hanqing Lu
IPC分类号： G06K9/00 , G06K9/46 , G06F17/30 , G06K9/62
CPC分类号： G06K9/4633 , G06F17/30256 , G06F17/30268 , G06F17/30271 , G06K9/4671 , G06K9/6215
摘要： An image matching method based on cascaded binary encoding includes using a hashing look-up with multiple hashing tables to coarsely filter candidate key-points in an image to produce a candidate subset of key-points, projecting the candidate subset into a high-dimensional Hamming space, and building a “Hamming distance-memory address” hashing table. An optimal matching key-point is discovered by querying the hashing table. The image matching method has high processing speed and matching quality, which can be used for efficient and accurate image matching.

96. 发明授权

US09966932B2 Parallel filtering method and corresponding apparatus 有权
公开(公告)号：US09966932B2
公开(公告)日：2018-05-08
申请号：US14785359
申请日：2013-04-19
申请人： Institute of Automation, Chinese Academy of Sciences
发明人： Donglin Wang , Leizu Yin , Yongyong Yang , Shaolin Xie , Tao Wang
IPC分类号： G06F17/10 , H03H17/02
CPC分类号： H03H17/0223 , H03H2017/0245 , H03H2218/10
摘要： An apparatus for parallel filtering, including a multi-granularity memory, a data cache device, a coefficient buffer broadcast device, a vector operation device and a command queue device. The multi-granularity memory is configured to store data to be filtered, filter coefficients and filtering result data. The data cache device is configured to cache, read and update the data to be filtered. The coefficient buffer broadcast device is configured to cache and broadcast the read filter coefficients. The command queue device is configured to store and output a queue of operation commands for the parallel filtering operation. The vector operation device is configured to perform a vector operation based on the data to be filtered and the output coefficient data, and write an operation result into the multi-granularity filtering result storage unit. A method is also provided. The apparatus and method have a fast filtering speed, a smaller number of accesses, an improved usage efficiency, a reduced power consumption and a wide application scope.

97. 发明授权

US09886775B2 Method for detecting horizontal and gravity directions of an image 有权
公开(公告)号：US09886775B2
公开(公告)日：2018-02-06
申请号：US15306980
申请日：2014-04-28
申请人： Institute of Automation Chinese Academy of Sciences
发明人： Zhiqiang Cao , Xilong Liu , Chao Zhou , Min Tan , Kun Ai
IPC分类号： G06K9/00 , G06T7/60
CPC分类号： G06T7/60 , G06T7/70 , G06T2207/10004 , G06T2207/20021 , G06T2207/20084 , G06T2207/30244 , G06T2207/30252
摘要： The disclosure relates to a method for detection of the horizontal and gravity directions of an image, the method comprising: selecting equidistant sampling points in an image at an interval of the radius of the sampling circle of an attention focus detector; placing the center of the sampling circle of the attention focus detector on each of the sampling points, and using the attention focus detector to acquire attention focus coordinates and the corresponding significant orientation angle, and all the attention focus coordinates and the corresponding significant orientation angles constitute a set Ωp; using an orientation perceptron to determine a local orientation angle and a weight at the attention focus according to the gray image information, and generating a local orientation function; obtaining a sum of each of the local orientation functions as an image direction function; obtaining a function MCGCS(β), and further obtaining the horizontal and gravity identification angles.

98. 发明申请

US20170329314A1 MODBUS TCP COMMUNICATION BEHAVIOUR ANOMALY DETECTION METHOD BASED ON OCSVM DUAL-OUTLINE MODEL 审中-公开
公开(公告)号：US20170329314A1
公开(公告)日：2017-11-16
申请号：US15527208
申请日：2014-12-30
申请人： SHENYANG INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES
发明人： Wenli SHANG , Jianming ZHAO , Ming WAN , Peng ZENG , Haibin YU
IPC分类号： G05B19/418 , H04L12/40
CPC分类号： G05B19/4185 , H04L12/40 , H04L12/40039 , H04L29/06 , H04L63/1425 , H04L2012/40228
摘要： Proposed is an anomaly detection method for communication behaviours in an industrial control system based on an OCSVM algorithm. According to the present invention, a normal behaviour profile model and an abnormal behaviour profile model, i.e. a dual-outline model, of communication behaviours in an industrial control system are established, parameter optimization is performed by means of a particle swarm optimization (PSO) algorithm, an optimal intrusion detection model is obtained, and abnormal Modbus TCP communication traffic is identified. According to the present invention, the false alarm rate is reduced by means of cooperative discrimination of the dual-outline detection model, the efficiency and reliability of anomaly detection are improved, and the method is more applicable to practical applications.

99. 发明申请

US20170224246A1 Method and System for Brain Activity Detection 审中-公开
公开(公告)号：US20170224246A1
公开(公告)日：2017-08-10
申请号：US15501978
申请日：2014-08-06
申请人： Institute of Automation Chinese Academy of Sciences
发明人： Tianzi Jiang , Xin Zhang , Nianming Zuo , Juanning Si , Ruirui Zhao , Jian Yu
IPC分类号： A61B5/0478 , A61B5/00 , A61B5/145
CPC分类号： A61B5/0478 , A61B5/0476 , A61B5/14542 , A61B5/14553 , A61B5/6803 , A61B5/7203 , A61B5/7225 , A61B5/7246 , A61B5/725 , A61B2562/066
摘要： Disclosed are a method and system for brain activity detection. The method is: performing multi-channel synchronous collections of brain electrical signals and cerebral cortex blood oxygen signals simultaneously, and ensuring synchronicity of the collected signals among channels, and collecting said brain electrical signals and said cerebral cortex blood oxygen signals of all locations at the same time. The system comprises: a functional near-infrared light source emission module (2) which employs the frequency division multiplexing technique, wherein the light source is modulated by carrier of different frequencies, said signal is accessed from the multi-functional joint collection helmet (1) through a transmission optical fiber to irradiate the scalp, and after being scattered and absorbed by the brain, the attenuated light signal is processed by the functional near-infrared detection module (3); the functional near-infrared detection module (3) is used for detecting weak optical signals of the scalp; the brain electricity detection module (4) is used for detecting weak electrical signals of the scalp; the central control unit (5) is used for synchronizing and fusing data flows, sending control commands to each functional module, and uploading data to the host computer (6). The method and system can control the interference to be the minimum and have good time scale consistency.

100. 发明申请

US20160162290A1 Processor with Polymorphic Instruction Set Architecture 审中-公开
标题翻译：具有多态指令集架构的处理器
公开(公告)号：US20160162290A1
公开(公告)日：2016-06-09
申请号：US14785385
申请日：2013-04-19
申请人： INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES
发明人： Donglin Wang , Shaolin Xie , Yongyong Yang , Leizu Yin , Lei Wang , Zijun Liu , Tao Wang , Xing Zhang
IPC分类号： G06F9/30
CPC分类号： G06F9/30
摘要： The present disclosure provides a processor having polymorphic instruction set architecture. The processor comprises a scalar processing unit, at least one polymorphic instruction processing unit, at least one multi-granularity parallel memory and a DMA controller. The polymorphic instruction processing unit comprises at least one functional unit. The polymorphic instruction processing unit is configured to interpret and execute a polymorphic instruction and the functional unit is configured to perform specific data operation tasks. The scalar processing unit is configured to invoke the polymorphic instruction and inquire an execution state of the polymorphic instruction. The DMA controller is configured to transmit configuration information for the polymorphic instruction and transmit data required by the polymorphic instruction to the multi-granularity parallel memory. With the present disclosure, programmers can redefine a processor instruction set based on algorithm characteristics of applications after tape-out of a processor.
摘要翻译：本公开提供了具有多态指令集架构的处理器。处理器包括标量处理单元，至少一个多态指令处理单元，至少一个多粒度并行存储器和DMA控制器。多态指令处理单元包括至少一个功能单元。多态指令处理单元被配置为解释并执行多态指令，并且功能单元被配置为执行特定的数据操作任务。标量处理单元被配置为调用多态指令并查询多态指令的执行状态。 DMA控制器被配置为发送多态指令的配置信息并将多态指令所需的数据发送到多粒度并行存储器。利用本公开，程序员可以在处理器输出之后基于应用的算法特性来重新定义处理器指令集。

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