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1. 发明申请

WO2015123647A1 OBJECT INGESTION THROUGH CANONICAL SHAPES, SYSTEMS AND METHODS 审中-公开
标题翻译：通过标准形状，系统和方法的对象注入
公开(公告)号：WO2015123647A1
公开(公告)日：2015-08-20
申请号：PCT/US2015/016069
申请日：2015-02-16
申请人： NANT HOLDINGS IP, LLC
发明人： WNUK, Kamil , MCKINNON, David , SUDOL, Jeremi , SONG, Bing , SIDDIQUI, Matheen
IPC分类号： G06K9/68 , G06K9/70
CPC分类号： G06K9/3241 , G06F17/30256 , G06F17/30259 , G06F17/30268 , G06F17/30277 , G06K9/00201 , G06K9/00744 , G06K9/4609 , G06T7/13 , G06T7/60 , G06T2207/20061 , G06T2207/20116
摘要： An object recognition ingestion system is presented. The object ingestion system captures image data of objects, possibly in an uncontrolled setting. The image data is analyzed to determine if one or more a priori know canonical shape objects match the object represented in the image data. The canonical shape object also includes one or more reference PoVs indicating perspectives from which to analyze objects having the corresponding shape. An object ingestion engine combines the canonical shape object along with the image data to create a model of the object. The engine generates a desirable set of model PoVs from the reference PoVs, and then generates recognition descriptors from each of the model PoVs. The descriptors, image data, model PoVs, or other contextually relevant information are combined into key frame bundles having sufficient information to allow other computing devices to recognize the object at a later time.
摘要翻译：提出了一种物体识别摄取系统。物体摄取系统捕获物体的图像数据，可能在不受控制的环境中。分析图像数据以确定一个或多个先验知道的规范形状对象是否与图像数据中表示的对象相匹配。规范形状对象还包括一个或多个参考PoV，其指示从其分析具有相应形状的对象的透视图。对象摄取引擎将规范形状对象与图像数据一起组合以创建对象的模型。引擎从参考PoV生成一组所需的模型PoV，然后从每个模型PoV生成识别描述符。描述符，图像数据，模型PoV或其他上下文相关信息被组合成具有足够信息的关键帧束，以允许其他计算设备在稍后的时间识别对象。

2. 发明申请

WO2018094360A9 METHODS AND SYSTEMS FOR PREDICTING DNA ACCESSIBILITY IN THE PAN-CANCER GENOME 审中-公开
公开(公告)号：WO2018094360A9
公开(公告)日：2018-05-24
申请号：PCT/US2017/062626
申请日：2017-11-20
申请人： NANTOMICS, LLC , NANT HOLDINGS IP, LLC
发明人： WNUK, Kamil , SUDOL, Jeremi , RABIZADEH, Shahrooz , SOON-SHIONG, Patrick , SZETO, Christopher , VASKE, Charles
IPC分类号： G06F19/24 , G06F19/12 , G06F19/26 , C12Q1/68
摘要： Techniques are provided for predicting DNA accessibility. DNase-seq data files and RNA-seq data files for a plurality of cell types are paired by assigning DNase-seq data files to RNA-seq data files that are at least within a same biotype. A neural network is configured to be trained using batches of the paired data files, where configuring the neural network comprises configuring convolutional layers to process a first input comprising DNA sequence data from a paired data file to generate a convolved output, and fully connected layers following the convolutional layers to concatenate the convolved output with a second input comprising gene expression levels derived from RNA-seq data from the paired data file and process the concatenation to generate a DNA accessibility prediction output. The trained neural network is used to predict DNA accessibility in a genomic sample input comprising RNA-seq data and whole genome sequencing for a new cell type.

3. 发明申请

WO2015119674A3 WIDE AREA AUGMENTED REALITY LOCATION-BASED SERVICES 审中-公开
公开(公告)号：WO2015119674A3
公开(公告)日：2015-08-13
申请号：PCT/US2014/061283
申请日：2014-10-19
申请人： NANT HOLDINGS IP, LLC
发明人： MCKINNON, David , WNUK, Kamil , SUDOL, Jeremi , SIDDIQUI, Matheen , WIACEK, John , SONG, Bing , WITCHEY, Nicholas J.
IPC分类号： G06T19/00 , G06F17/30
摘要： Apparatus, methods and systems of providing AR content are disclosed. Embodiments of the inventive subject matter can obtain an initial map of an area, derive views of interest, obtain AR content objects associated with the views of interest, establish experience clusters and generate a tile map tessellated based on the experience clusters. A user device could be configured to obtain and instantiate at least some of the AR content objects based on at least one of a location and a recognition.

4. 发明申请

WO2018094360A3 METHODS AND SYSTEMS FOR PREDICTING DNA ACCESSIBILITY IN THE PAN-CANCER GENOME 审中-公开
公开(公告)号：WO2018094360A3
公开(公告)日：2018-05-24
申请号：PCT/US2017/062626
申请日：2017-11-20
申请人： NANTOMICS, LLC , NANT HOLDINGS IP, LLC
发明人： WNUK, Kamil , SUDOL, Jeremi , RABIZADEH, Shahrooz , SOON-SHIONG, Patrick , SZETO, Christopher , VASKE, Charles
IPC分类号： G06F19/24 , G06F19/12 , G06F19/26 , C12Q1/68
摘要： Techniques are provided for predicting DNA accessibility. DNase-seq data files and RNA-seq data files for a plurality of cell types are paired by assigning DNase-seq data files to RNA-seq data files that are at least within a same biotype. A neural network is configured to be trained using batches of the paired data files, where configuring the neural network comprises configuring convolutional layers to process a first input comprising DNA sequence data from a paired data file to generate a convolved output, and fully connected layers following the convolutional layers to concatenate the convolved output with a second input comprising gene expression levels derived from RNA-seq data from the paired data file and process the concatenation to generate a DNA accessibility prediction output. The trained neural network is used to predict DNA accessibility in a genomic sample input comprising RNA-seq data and whole genome sequencing for a new cell type.

5. 发明申请

WO2018094360A2 METHODS AND SYSTEMS FOR PREDICTING DNA ACCESSIBILITY IN THE PAN-CANCER GENOME 审中-公开
公开(公告)号：WO2018094360A2
公开(公告)日：2018-05-24
申请号：PCT/US2017/062626
申请日：2017-11-20
申请人： NANTOMICS, LLC , NANT HOLDINGS IP, LLC , WNUK, Kamil , SUDOL, Jeremi , RABIZADEH, Shahrooz
发明人： WNUK, Kamil , SUDOL, Jeremi , RABIZADEH, Shahrooz , SOON-SHIONG, Patrick , SZETO, Christopher , VASKE, Charles
IPC分类号： G06F19/24 , G06F19/12 , G06F19/26 , C12Q1/68
摘要： Techniques are provided for predicting DNA accessibility. DNase-seq data files and RNA-seq data files for a plurality of cell types are paired by assigning DNase-seq data files to RNA-seq data files that are at least within a same biotype. A neural network is configured to be trained using batches of the paired data files, where configuring the neural network comprises configuring convolutional layers to process a first input comprising DNA sequence data from a paired data file to generate a convolved output, and fully connected layers following the convolutional layers to concatenate the convolved output with a second input comprising gene expression levels derived from RNA-seq data from the paired data file and process the concatenation to generate a DNA accessibility prediction output. The trained neural network is used to predict DNA accessibility in a genomic sample input comprising RNA-seq data and whole genome sequencing for a new cell type.

6. 发明申请

WO2015127117A1 INVARIANT-BASED DIMENSIONAL REDUCTION OF OBJECT RECOGNITION FEATURES, SYSTEMS AND METHODS 审中-公开
标题翻译：目标识别特征，系统和方法的基于不变的尺寸减小
公开(公告)号：WO2015127117A1
公开(公告)日：2015-08-27
申请号：PCT/US2015/016677
申请日：2015-02-19
申请人： NANT HOLDINGS IP, LLC
发明人： WNUK, Kamil , SUDOL, Jeremi , SONG, Bing , MCKINNON, David , SIDDIQUI, Matheen
IPC分类号： G06K9/62 , G06K9/20
CPC分类号： G06K9/6232 , G06K9/4633 , G06K9/4671 , G06K9/623
摘要： A sensor data processing system and method is described. Contemplated systems and methods derive a first recognition trait of an object from a first data set that represents the object in a first environmental state. A second recognition trait of the object is then derived from a second data set that represents the object in a second environmental state. The sensor data processing systems and methods then identifies a mapping of elements of the first and second recognition traits in a new representation space. The mapping of elements satisfies a variance criterion for corresponding elements, which allows the mapping to be used for object recognition. The sensor data processing systems and methods described herein provide new object recognition techniques that are computationally efficient and can be performed in real-time by the mobile phone technology that is currently available.
摘要翻译：描述传感器数据处理系统和方法。考虑的系统和方法从表示第一环境状态中的对象的第一数据集导出对象的第一识别特征。然后从表示第二环境状态中的对象的第二数据集导出对象的第二识别特征。然后，传感器数据处理系统和方法在新的表示空间中识别第一和第二识别特征的元素的映射。元素的映射满足相应元素的方差标准，这允许映射用于对象识别。本文描述的传感器数据处理系统和方法提供了新的对象识别技术，其在计算上是有效的并且可以通过当前可用的移动电话技术实时地执行。

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