公开(公告)号：US20240402298A1

公开(公告)日：2024-12-05

申请号：US17382931

申请日：2021-07-22

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Hui HUANG ,  Yi LI ,  Erik BLASCH ,  Khanh PHAM ,  Jiaoyue LIU ,  Nichole SULLIVAN ,  Dan SHEN ,  Genshe CHEN

IPC: G01S7/41 ,  G01S7/40

Abstract: A method for recognizing a low-probability-of-interception (LPI) radar signal waveform includes: obtaining, by a radar signal receiver, an LPI radar signal s(t), s(t) varying with time t; extracting, by a radar signal processor, an adaptive feature and a pre-defined analytical feature from the LPI radar signal s(t); combining, by the radar signal processor, the adaptive feature with the pre-defined analytical feature to generate a constructed adaptive feature; and applying, by the radar signal processor, a convolutional neural network (CNN) model to classify the constructed adaptive feature to recognize the LPI radar signal waveform.

公开(公告)号：US20230186120A1

公开(公告)日：2023-06-15

申请号：US17534754

申请日：2021-11-24

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Qingliang ZHAO ,  Jiaoyue LIU ,  Nichole SULLIVAN ,  Kuochu CHANG ,  Erik BLASCH ,  Genshe CHEN

IPC: G06N5/04 ,  G06N5/02 ,  G06F40/295 ,  G06F40/30 ,  G06F16/25 ,  G06F16/26

CPC classification number: G06N5/04 ,  G06F16/26 ,  G06F16/258 ,  G06F40/30 ,  G06F40/295 ,  G06N5/022

Abstract: A computing system includes: a memory, containing instructions for a method for anomaly and pattern detection of unstructured big data via semantic analysis and dynamic knowledge graph construction; a processor, coupled with the memory and, when the instructions being executed, configured to: receive unstructured big data associated with social network interactions, events, or activities; parse and structure the unstructured big data to generate structured big data; form a dynamic knowledge base based on the structured big data; and perform sematic reasoning on the dynamic knowledge base to discover patterns and anomalies among the social network interactions, events, or activities; and a display, comprising an interactive graphical user interface (GUI), configured to receive the anomalies and patterns to display real-time actionable alerts, provide recommendations, and support decisions.

公开(公告)号：US20230040237A1

公开(公告)日：2023-02-09

申请号：US17876908

申请日：2022-07-29

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Hua-mei CHEN ,  Bora SUL ,  Genshe CHEN ,  Erik BLASCH ,  Khanh PHAM

IPC: G06T7/00 ,  G06V10/80 ,  G06V10/82

Abstract: A method for detecting fake images includes: obtaining an image for authentication, and hand-crafting a multi-attribute classifier to determine whether the image is authentic. Hand-crafting the multi-attribute classifier includes fusing at least an image classifier, an image spectrum classifier, a co-occurrence matrix classifier, and a one-dimensional (1D) power spectrum density (PSD) classifier. The multi-attribute classifier is trained by pre-processing training images to generate an attribute-specific training dataset to train each of the image classifier, the image spectrum classifier, the co-occurrence matrix classifier, and the 1D PSD classifier.

公开(公告)号：US20210103841A1

公开(公告)日：2021-04-08

申请号：US16595107

申请日：2019-10-07

Applicant: INTELLIGENT FUSION TECHNOLOGY, INC.

Inventor： Dan SHEN ,  Carolyn SHEAFF ,  Jingyang LU ,  Genshe CHEN ,  Erik BLASCH ,  Khanh PHAM

IPC: G06N7/00 ,  G06N20/00 ,  B64G3/00

Abstract: A method for rapid discovery of satellite behavior, applied to a pursuit-evasion system including at least one satellite and a plurality of space sensing assets. The method includes performing transfer learning and zero-shot learning to obtain a semantic layer using space data information. The space data information includes simulated space data based on a physical model. The method further includes obtaining measured space-activity data of the satellite from the space sensing assets; performing manifold learning on the measured space-activity data to obtain measured state-related parameters of the satellite; modeling the state uncertainty and the uncertainty propagation of the satellite based on the measured state-related parameters; and performing game reasoning based on a Markov game model to predict satellite behavior and management of the plurality of space sensing assets according to the semantic layer and the modeled state uncertainty and uncertainty propagation.

公开(公告)号：US20190228272A1

公开(公告)日：2019-07-25

申请号：US15878188

申请日：2018-01-23

Applicant: Intelligent Fusion Technology, Inc

Inventor： Dan SHEN ,  Peter ZULCH ,  Marcello DISASIO ,  Erik BLASCH ,  Genshe CHEN ,  Zhonghai WANG ,  Jingyang LU

IPC: G06K9/62 ,  G06N7/08 ,  G06K9/68 ,  G06T7/80 ,  G01S13/58 ,  H04N5/33

Abstract: The present disclosure provides a method for joint manifold learning based heterogenous sensor data fusion, comprising: obtaining learning heterogeneous sensor data from a plurality sensors to form a joint manifold, wherein the plurality sensors include different types of sensors that detect different characteristics of targeting objects; performing, using a hardware processor, a plurality of manifold learning algorithms to process the joint manifold to obtain raw manifold learning results, wherein a dimension of the manifold learning results is less than a dimension of the joint manifold; processing the raw manifold learning results to obtain intrinsic parameters of the targeting objects; evaluating the multiple manifold learning algorithms based on the raw manifold learning results and the intrinsic parameters to determine one or more optimum manifold learning algorithms; and applying the one or more optimum manifold learning algorithms to fuse heterogeneous sensor data generated by the plurality sensors.