Patents by Inventor Marcus O. Freitag
Marcus O. Freitag has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11527062Abstract: A computer-implemented method for determining field boundaries and crop forecasts in each field is provided. The method includes deriving vegetation indices for each geo-spatial pixel of each image of multi-spectral imagery at a plurality of points in time, constructing minimum bounding boxes for each image according to the vegetation indices, and generating, based on a neural network analysis of each image and the minimum bounding boxes, a geo-spatial plot of crops including a predicted plot of future crop usage for an area including each field in the multi-spectral imagery.Type: GrantFiled: March 27, 2020Date of Patent: December 13, 2022Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Conrad M. Albrecht, Siyuan Lu, Fernando J. Marianno, Hendrik F. Hamann, Marcus O. Freitag, Levente I. Klein
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Patent number: 11210268Abstract: A database system includes a processing sub-system having an electronic hardware controller that receives first formatted data, and an electronic file formatting sub-system having an electronic hardware controller that assigns coordinate values corresponding to a second data format to the first formatted data. The file formatting sub-system generates a dual-format data file that fuses together the first formatted data with the coordinate values corresponding to a second data format. The database system further includes a storage sub-system having a data storage unit configured to store the dual-format data file.Type: GrantFiled: November 17, 2017Date of Patent: December 28, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Conrad M. Albrecht, Marcus O. Freitag, Hendrik F. Hamann
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Patent number: 11204896Abstract: A database system includes a processing sub-system having an electronic hardware controller that receives first formatted data, and an electronic file formatting sub-system having an electronic hardware controller that assigns coordinate values corresponding to a second data format to the first formatted data. The file formatting sub-system generates a dual-format data file that fuses together the first formatted data with the coordinate values corresponding to a second data format. The database system further includes a storage sub-system having a data storage unit configured to store the dual-format data file.Type: GrantFiled: August 18, 2017Date of Patent: December 21, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Conrad M. Albrecht, Marcus O. Freitag, Hendrik F. Hamann
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Patent number: 11151379Abstract: A computer-implemented method for crop type identification using satellite observation and weather data. The method includes extracting current and historical data from pixels of satellite images of a target region, generating temporal sequences of vegetation indices, based on the weather data, converting each timestamp of the temporal sequences into a modified temporal variable correlating with actual crop growth, training a classifier using a set of historical temporal sequences of vegetation indices with respect to the modified temporal variable as training features and corresponding historically known crop types as training labels, identifying a crop type for each pixel location within the satellite images using the trained classifier and the historical temporal sequences of vegetation indices with respect to the modified temporal variable for a current crop season, and estimating a crop acreage value by aggregating identified pixels associated with the crop type.Type: GrantFiled: September 16, 2019Date of Patent: October 19, 2021Assignee: International Business Machines CorporationInventors: Marcus O. Freitag, Hendrik F. Hamann, Levente Klein, Siyuan Lu
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Patent number: 10839264Abstract: Scalable feature classification for 3D point cloud data is provided. In one aspect, a method for rasterizing 3D point cloud data includes: obtaining the 3D point cloud data; generating a digital elevation model (DEM) from the 3D point cloud data; decomposing the DEM into local and global fluctuations to obtain a local DEM; generating geo-referenced shapes by automatically thresholding the local DEM; cropping and normalizing the local DEM using minimum bounding boxes derived from the geo-referenced shapes and manual annotations from subject matter experts to create a cropped DEM; and linking geo-spatially tagged labels from the subject matter experts to the cropped DEM. These data can be then directly fed into a system having an ensemble of artificial neural networks. By way of example, a scalable ecosystem is presented on the basis of the geo-spatial platform IBM PAIRS.Type: GrantFiled: November 9, 2018Date of Patent: November 17, 2020Assignee: International Business Machines CorporationInventors: Conrad M. Albrecht, Sharathchandra Pankanti, Marcus O. Freitag, Hendrik F. Hamann
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Publication number: 20200226375Abstract: A computer-implemented method for determining field boundaries and crop forecasts in each field is provided. The method includes deriving vegetation indices for each geo-spatial pixel of each image of multi-spectral imagery at a plurality of points in time, constructing minimum bounding boxes for each image according to the vegetation indices, and generating, based on a neural network analysis of each image and the minimum bounding boxes, a geo-spatial plot of crops including a predicted plot of future crop usage for an area including each field in the multi-spectral imagery.Type: ApplicationFiled: March 27, 2020Publication date: July 16, 2020Inventors: Conrad M. Albrecht, Siyuan Lu, Fernando J. Marianno, Hendrik F. Hamann, Marcus O. Freitag, Levente I. Klein
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Patent number: 10664702Abstract: A computer-implemented method for determining farm boundary delineations within a target geographic area, comprising extracting data from pixels of a satellite image of the target geographic area, evaluating the data using a classification algorithm to generate one or more line segments between adjacent pixels, the one or more line segments being representative of a portion of a boundary delineation, connecting the one or more line segments to an adjacent line segment to form a boundary delineation defining at least one parcel of land within the target geographic area, and generating a boundary delineation map including the boundary delineation.Type: GrantFiled: August 31, 2018Date of Patent: May 26, 2020Assignee: International Business Machines CorporationInventors: Conrad M. Albrecht, Siyuan Lu, Fernando J. Marianno, Hendrik F. Hamann, Marcus O. Freitag, Levente I. Klein
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Publication number: 20200151504Abstract: Scalable feature classification for 3D point cloud data is provided. In one aspect, a method for rasterizing 3D point cloud data includes: obtaining the 3D point cloud data; generating a digital elevation model (DEM) from the 3D point cloud data; decomposing the DEM into local and global fluctuations to obtain a local DEM; generating geo-referenced shapes by automatically thresholding the local DEM; cropping and normalizing the local DEM using minimum bounding boxes derived from the geo-referenced shapes and manual annotations from subject matter experts to create a cropped DEM; and linking geo-spatially tagged labels from the subject matter experts to the cropped DEM. These data can be then directly fed into a system having an ensemble of artificial neural networks. By way of example, a scalable ecosystem is presented on the basis of the geo-spatial platform IBM PAIRS.Type: ApplicationFiled: November 9, 2018Publication date: May 14, 2020Inventors: Conrad M. Albrecht, Sharathchandra Pankanti, Marcus O. Freitag, Hendrik F. Hamann
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Patent number: 10586105Abstract: A computer-implemented method for crop type identification using satellite observation and weather data. The method includes extracting current and historical data from pixels of satellite images of a target region, generating temporal sequences of vegetation indices, based on the weather data, converting each timestamp of the temporal sequences into a modified temporal variable correlating with actual crop growth, training a classifier using a set of historical temporal sequences of vegetation indices with respect to the modified temporal variable as training features and corresponding historically known crop types as training labels, identifying a crop type for each pixel location within the satellite images using the trained classifier and the historical temporal sequences of vegetation indices with respect to the modified temporal variable for a current crop season, and estimating a crop acreage value by aggregating identified pixels associated with the crop type.Type: GrantFiled: December 30, 2016Date of Patent: March 10, 2020Assignee: International Business Machines CorporationInventors: Marcus O. Freitag, Hendrik F. Hamann, Levente Klein, Siyuan Lu
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Publication number: 20200012853Abstract: A computer-implemented method for crop type identification using satellite observation and weather data. The method includes extracting current and historical data from pixels of satellite images of a target region, generating temporal sequences of vegetation indices, based on the weather data, converting each timestamp of the temporal sequences into a modified temporal variable correlating with actual crop growth, training a classifier using a set of historical temporal sequences of vegetation indices with respect to the modified temporal variable as training features and corresponding historically known crop types as training labels, identifying a crop type for each pixel location within the satellite images using the trained classifier and the historical temporal sequences of vegetation indices with respect to the modified temporal variable for a current crop season, and estimating a crop acreage value by aggregating identified pixels associated with the crop type.Type: ApplicationFiled: September 16, 2019Publication date: January 9, 2020Inventors: Marcus O. Freitag, Hendrik F. Hamann, Levente Klein, Siyuan Lu
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Patent number: 10410091Abstract: A computer-implemented method includes receiving one or more training images depicting one or more training geographical regions. One or more environmental characteristic (EC) values are determined for the training images. The EC values include at least one EC value for each of the training images. One or more models are generated for mapping an EC value of an image to a determination of whether an artifact is present in a geographical region depicted by the image, based on the EC values and based on knowledge of which of the training images depict training geographical regions having artifacts present. A new image is received depicting a new geographical region. The models are applied to the new image. A probability that a new artifact is present in the new geographical region depicted in the new image is determined, based on the applying the models to the new image.Type: GrantFiled: August 10, 2017Date of Patent: September 10, 2019Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Conrad M. Albrecht, Marcus O. Freitag, Hendrik F. Hamann, Sharathchandra U. Pankanti
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Patent number: 10372705Abstract: An embodiment includes dividing a map into a first grid comprising a first plurality of cells with a first resolution and into a second grid comprising a second plurality of cells with a second resolution; determining that, because an initial portion of a key of a first cell of the second grid comprises a key of a first cell of the first grid, the first cell of the first grid comprises the first cell of the second grid; storing the first and the second grid in memories of distributed servers, wherein the first cell of the first grid and the first cell of the second grid are stored in a same one of the distributed servers or are stored in neighboring ones of the distributed servers; and directing respective processors of the distributed servers to perform a parallel search of the first grid and the second grid using the keys.Type: GrantFiled: April 11, 2016Date of Patent: August 6, 2019Assignee: International Business Machines CorporationInventors: Sergio A. Bermudez Rodriguez, Marcus O. Freitag, Hendrik F. Hamann, Levente Klein, Fernando J. Marianno
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Publication number: 20190057110Abstract: A database system includes a processing sub-system having an electronic hardware controller that receives first formatted data, and an electronic file formatting sub-system having an electronic hardware controller that assigns coordinate values corresponding to a second data format to the first formatted data. The file formatting sub-system generates a dual-format data file that fuses together the first formatted data with the coordinate values corresponding to a second data format. The database system further includes a storage sub-system having a data storage unit configured to store the dual-format data file.Type: ApplicationFiled: November 17, 2017Publication date: February 21, 2019Inventors: Conrad M. Albrecht, Marcus O. Freitag, Hendrik F. Hamann
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Publication number: 20190057109Abstract: A database system includes a processing sub-system having an electronic hardware controller that receives first formatted data, and an electronic file formatting sub-system having an electronic hardware controller that assigns coordinate values corresponding to a second data format to the first formatted data. The file formatting sub-system generates a dual-format data file that fuses together the first formatted data with the coordinate values corresponding to a second data format. The database system further includes a storage sub-system having a data storage unit configured to store the dual-format data file.Type: ApplicationFiled: August 18, 2017Publication date: February 21, 2019Inventors: Conrad M. Albrecht, Marcus O. Freitag, Hendrik F. Hamann
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Publication number: 20190050687Abstract: A computer-implemented method includes receiving one or more training images depicting one or more training geographical regions. One or more environmental characteristic (EC) values are determined for the training images. The EC values include at least one EC value for each of the training images. One or more models are generated for mapping an EC value of an image to a determination of whether an artifact is present in a geographical region depicted by the image, based on the EC values and based on knowledge of which of the training images depict training geographical regions having artifacts present. A new image is received depicting a new geographical region. The models are applied to the new image. A probability that a new artifact is present in the new geographical region depicted in the new image is determined, based on the applying the models to the new image.Type: ApplicationFiled: August 10, 2017Publication date: February 14, 2019Inventors: Conrad M. Albrecht, Marcus O. Freitag, Hendrik F. Hamann, Sharathchandra U. Pankanti
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Publication number: 20180373932Abstract: A computer-implemented method for determining farm boundary delineations within a target geographic area, comprising extracting data from pixels of a satellite image of the target geographic area, evaluating the data using a classification algorithm to generate one or more line segments between adjacent pixels, the one or more line segments being representative of a portion of a boundary delineation, connecting the one or more line segments to an adjacent line segment to form a boundary delineation defining at least one parcel of land within the target geographic area, and generating a boundary delineation map including the boundary delineation.Type: ApplicationFiled: August 31, 2018Publication date: December 27, 2018Inventors: Conrad M. Albrecht, Siyuan Lu, Fernando J. Marianno, Hendrik F. Hamann, Marcus O. Freitag, Levente I. Klein
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Publication number: 20180189564Abstract: A computer-implemented method for crop type identification using satellite observation and weather data. The method includes extracting current and historical data from pixels of satellite images of a target region, generating temporal sequences of vegetation indices, based on the weather data, converting each timestamp of the temporal sequences into a modified temporal variable correlating with actual crop growth, training a classifier using a set of historical temporal sequences of vegetation indices with respect to the modified temporal variable as training features and corresponding historically known crop types as training labels, identifying a crop type for each pixel location within the satellite images using the trained classifier and the historical temporal sequences of vegetation indices with respect to the modified temporal variable for a current crop season, and estimating a crop acreage value by aggregating identified pixels associated with the crop type.Type: ApplicationFiled: December 30, 2016Publication date: July 5, 2018Inventors: Marcus O. Freitag, Hendrik F. Hamann, Levente Klein, Siyuan Lu
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Publication number: 20170011089Abstract: An embodiment includes dividing a map into a first grid comprising a first plurality of cells with a first resolution and into a second grid comprising a second plurality of cells with a second resolution; determining that, because an initial portion of a key of a first cell of the second grid comprises a key of a first cell of the first grid, the first cell of the first grid comprises the first cell of the second grid; storing the first and the second grid in memories of distributed servers, wherein the first cell of the first grid and the first cell of the second grid are stored in a same one of the distributed servers or are stored in neighboring ones of the distributed servers; and directing respective processors of the distributed servers to perform a parallel search of the first grid and the second grid using the keys.Type: ApplicationFiled: April 11, 2016Publication date: January 12, 2017Inventors: Sergio A. Bermudez Rodriguez, Marcus O. Freitag, Hendrik F. Hamann, Levente Klein, Fernando J. Marianno
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Patent number: 9236250Abstract: A single crystalline silicon carbide layer can be grown on a single crystalline sapphire substrate. Subsequently, a graphene layer can be formed by conversion of a surface layer of the single crystalline silicon layer during an anneal at an elevated temperature in an ultrahigh vacuum environment. Alternately, a graphene layer can be deposited on an exposed surface of the single crystalline silicon carbide layer. A graphene layer can also be formed directly on a surface of a sapphire substrate or directly on a surface of a silicon carbide substrate. Still alternately, a graphene layer can be formed on a silicon carbide layer on a semiconductor substrate. The commercial availability of sapphire substrates and semiconductor substrates with a diameter of six inches or more allows formation of a graphene layer on a commercially scalable substrate for low cost manufacturing of devices employing a graphene layer.Type: GrantFiled: June 21, 2013Date of Patent: January 12, 2016Assignee: GLOBALFOUNDRIES INC.Inventors: Jack O. Chu, Christos D. Dimitrakopoulos, Marcus O. Freitag, Alfred Grill, Timothy J. McArdle, Robert L. Wisnieff
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Patent number: 8877340Abstract: A graphene layer is formed on a crystallographic surface having a non-hexagonal symmetry. The crystallographic surface can be a surface of a single crystalline semiconductor carbide layer. The non-hexagonal symmetry surface of the single crystalline semiconductor carbide layer is annealed at an elevated temperature in ultra-high vacuum environment to form the graphene layer. During the anneal, the semiconductor atoms on the non-hexagonal surface of the single crystalline semiconductor carbide layer are evaporated selective to the carbon atoms. As the semiconductor atoms are selectively removed, the carbon concentration on the surface of the semiconductor-carbon alloy layer increases. Despite the non-hexagonal symmetry of the surface of the semiconductor-carbon alloy layer, the remaining carbon atoms can coalesce to form a graphene layer having hexagonal symmetry.Type: GrantFiled: July 27, 2010Date of Patent: November 4, 2014Assignee: International Business Machines CorporationInventors: Jack O. Chu, Christos Dimitrakopoulos, Marcus O. Freitag, Alfred Grill, Timothy J. McArdle, Chun-Yung Sung, Robert L. Wisnieff