Patents by Inventor Cody Gustave Berlin
Cody Gustave Berlin 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: 11670024Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.Type: GrantFiled: March 8, 2021Date of Patent: June 6, 2023Assignee: Neon Evolution Inc.Inventors: Cody Gustave Berlin, Carl Davis Bogan, III, Kenneth Michael Lande, Jacob Myles Laser, Brian Sung Lee, Anders Øland
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Publication number: 20230049729Abstract: Systems and methods are disclosed configured to train an autoencoder. A data training set is generated comprising images of different faces. A first autoencoder configuration is generated, comprising a first encoder, and a first decoder. The first autoencoder configuration is trained using dataset images, wherein weights associated with the first encoder and weights associated with the first decoder are modified. A second autoencoder configuration is generated comprising the first encoder and a second decoder. The second decoder is trained using images of a first target face. First encoder weights are substantially maintained, and weights associated with the second decoder are modified. An autoencoder comprising the trained first encoder and the trained second decoder generates an output using a source image of a first face having a facial expression, where the facial expression of the first face from the source image is applied to the first specific target face.Type: ApplicationFiled: April 7, 2022Publication date: February 16, 2023Inventors: Cody Gustave Berlin, Carl Davis Bogan, III, Kenneth Michael Lande, Anders Øland, Davide Toniolo, Alessia Bertugli, Dario Bertazioli, Brian Sung Lee
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Patent number: 11308657Abstract: Systems and methods are disclosed configured to train an autoencoder. A data training set is generated comprising images of different faces. A first autoencoder configuration is generated, comprising a first encoder, and a first decoder. The first autoencoder configuration is trained using dataset images, wherein weights associated with the first encoder and weights associated with the first decoder are modified. A second autoencoder configuration is generated comprising the first encoder and a second decoder. The second decoder is trained using a plurality of images of a first target face. First encoder weights are substantially maintained, and weights associated with the second decoder are modified. An autoencoder comprising the trained first encoder and the trained second decoder is used to generate an output using a source image of a first face having a facial expression, where the facial expression of the first face from the source image is applied to the first specific target face.Type: GrantFiled: August 11, 2021Date of Patent: April 19, 2022Assignee: Neon Evolution Inc.Inventors: Cody Gustave Berlin, Carl Davis Bogan, III, Kenneth Michael Lande, Anders Øland, Davide Toniolo, Alessia Bertugli, Dario Bertazioli, Brian Sung Lee
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Publication number: 20210334595Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.Type: ApplicationFiled: March 8, 2021Publication date: October 28, 2021Inventors: Cody Gustave Berlin, Carl Davis Bogan, III, Kenneth Michael Lande, Jacob Myles Laser, Brian Sung Lee, Anders Øland
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Patent number: 10949715Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.Type: GrantFiled: May 27, 2020Date of Patent: March 16, 2021Assignee: Neon Evolution Inc.Inventors: Cody Gustave Berlin, Carl Davis Bogan, III, Kenneth Michael Lande, Jacob Myles Laser, Brian Sung Lee, Anders Øland
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Publication number: 20210056348Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.Type: ApplicationFiled: May 27, 2020Publication date: February 25, 2021Inventors: Cody Gustave Berlin, Carl Davis Bogan, III, Kenneth Michael Lande, Jacob Myles Laser, Brian Sung Lee, Anders Øland
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Patent number: 10803646Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.Type: GrantFiled: December 2, 2019Date of Patent: October 13, 2020Assignee: Neon Evolution Inc.Inventors: Carl Davis Bogan, III, Kenneth Michael Lande, Jacob Myles Laser, Brian Sung Lee, Cody Gustave Berlin
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Patent number: 10671838Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.Type: GrantFiled: December 2, 2019Date of Patent: June 2, 2020Assignee: Neon Evolution Inc.Inventors: Carl Davis Bogan, III, Kenneth Michael Lande, Jacob Myles Laser, Brian Sung Lee, Cody Gustave Berlin
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Patent number: 10658005Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.Type: GrantFiled: December 2, 2019Date of Patent: May 19, 2020Assignee: Neon Evolution Inc.Inventors: Carl Davis Bogan, III, Kenneth Michael Lande, Jacob Myles Laser, Brian Sung Lee, Cody Gustave Berlin