Patents by Inventor Anting Shen
Anting Shen 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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Publication number: 20240125934Abstract: An annotation system uses annotations for a first set of sensor measurements from a first sensor to identify annotations for a second set of sensor measurements from a second sensor. The annotation system identifies reference annotations in the first set of sensor measurements that indicates a location of a characteristic object in the two-dimensional space. The annotation system determines a spatial region in the three-dimensional space of the second set of sensor measurements that corresponds to a portion of the scene represented in the annotation of the first set of sensor measurements. The annotation system determines annotations within the spatial region of the second set of sensor measurements that indicates a location of the characteristic object in the three-dimensional space.Type: ApplicationFiled: December 8, 2023Publication date: April 18, 2024Applicant: Tesla, Inc.Inventor: Anting Shen
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Publication number: 20240112051Abstract: Systems and methods include machine learning models operating at different frequencies. An example method includes obtaining images at a threshold frequency from one or more image sensors positioned about a vehicle. Location information associated with objects classified in the images is determined based on the images. The images are analyzed via a first machine learning model at the threshold frequency. For a subset of the images, the first machine learning model uses output information from a second machine learning model, the second machine learning model being performed at less than the threshold frequency.Type: ApplicationFiled: October 6, 2023Publication date: April 4, 2024Inventor: Anting Shen
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Patent number: 11908171Abstract: Systems and methods for enhanced object detection for autonomous vehicles based on field of view. An example method includes obtaining an image from an image sensor of one or more image sensors positioned about a vehicle. A field of view for the image is determined, with the field of view being associated with a vanishing line. A crop portion corresponding to the field of view is generated from the image, with a remaining portion of the image being downsampled. Information associated with detected objects depicted in the image is outputted based on a convolutional neural network, with detecting objects being based on performing a forward pass through the convolutional neural network of the crop portion and the remaining portion.Type: GrantFiled: December 22, 2022Date of Patent: February 20, 2024Assignee: Tesla, Inc.Inventors: Anting Shen, Romi Phadte, Gayatri Joshi
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Patent number: 11841434Abstract: An annotation system uses annotations for a first set of sensor measurements from a first sensor to identify annotations for a second set of sensor measurements from a second sensor. The annotation system identifies reference annotations in the first set of sensor measurements that indicates a location of a characteristic object in the two-dimensional space. The annotation system determines a spatial region in the three-dimensional space of the second set of sensor measurements that corresponds to a portion of the scene represented in the annotation of the first set of sensor measurements. The annotation system determines annotations within the spatial region of the second set of sensor measurements that indicates a location of the characteristic object in the three-dimensional space.Type: GrantFiled: June 10, 2022Date of Patent: December 12, 2023Assignee: Tesla, Inc.Inventor: Anting Shen
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Patent number: 11816585Abstract: Systems and methods include machine learning models operating at different frequencies. An example method includes obtaining images at a threshold frequency from one or more image sensors positioned about a vehicle. Location information associated with objects classified in the images is determined based on the images. The images are analyzed via a first machine learning model at the threshold frequency. For a subset of the images, the first machine learning model uses output information from a second machine learning model, the second machine learning model being performed at less than the threshold frequency.Type: GrantFiled: December 3, 2019Date of Patent: November 14, 2023Assignee: Tesla, Inc.Inventor: Anting Shen
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Publication number: 20230245415Abstract: Systems and methods for enhanced object detection for autonomous vehicles based on field of view. An example method includes obtaining an image from an image sensor of one or more image sensors positioned about a vehicle. A field of view for the image is determined, with the field of view being associated with a vanishing line. A crop portion corresponding to the field of view is generated from the image, with a remaining portion of the image being downsampled. Information associated with detected objects depicted in the image is outputted based on a convolutional neural network, with detecting objects being based on performing a forward pass through the convolutional neural network of the crop portion and the remaining portion.Type: ApplicationFiled: December 22, 2022Publication date: August 3, 2023Inventors: Anting Shen, Romi Phadte, Gayatri Joshi
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Publication number: 20230177819Abstract: An autonomous control system generates synthetic data that reflect simulated environments. Specifically, the synthetic data is a representation of sensor data of the simulated environment from the perspective of one or more sensors. The system generates synthetic data by introducing one or more simulated modifications to sensor data captured by the sensors or by simulating the sensor data for a virtual environment. The autonomous control system uses the synthetic data to train computer models for various detection and control algorithms. In general, this allows autonomous control systems to augment training data to improve performance of computer models, simulate scenarios that are not included in existing training data, and/or train computer models that remove unwanted effects or occlusions from sensor data of the environment.Type: ApplicationFiled: October 28, 2022Publication date: June 8, 2023Inventors: Forrest Nelson Iandola, Donald Benton MacMillen, Anting Shen, Harsimran Singh Sidhu, Paras Jagdish Jain
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Patent number: 11537811Abstract: Systems and methods for enhanced object detection for autonomous vehicles based on field of view. An example method includes obtaining an image from an image sensor of one or more image sensors positioned about a vehicle. A field of view for the image is determined, with the field of view being associated with a vanishing line. A crop portion corresponding to the field of view is generated from the image, with a remaining portion of the image being downsampled. Information associated with detected objects depicted in the image is outputted based on a convolutional neural network, with detecting objects being based on performing a forward pass through the convolutional neural network of the crop portion and the remaining portion.Type: GrantFiled: December 4, 2019Date of Patent: December 27, 2022Assignee: Tesla, Inc.Inventors: Anting Shen, Romi Phadte, Gayatri Joshi
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Publication number: 20220375208Abstract: An annotation system uses annotations for a first set of sensor measurements from a first sensor to identify annotations for a second set of sensor measurements from a second sensor. The annotation system identifies reference annotations in the first set of sensor measurements that indicates a location of a characteristic object in the two-dimensional space. The annotation system determines a spatial region in the three-dimensional space of the second set of sensor measurements that corresponds to a portion of the scene represented in the annotation of the first set of sensor measurements. The annotation system determines annotations within the spatial region of the second set of sensor measurements that indicates a location of the characteristic object in the three-dimensional space.Type: ApplicationFiled: June 10, 2022Publication date: November 24, 2022Inventor: Anting Shen
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Patent number: 11487288Abstract: An autonomous control system generates synthetic data that reflect simulated environments. Specifically, the synthetic data is a representation of sensor data of the simulated environment from the perspective of one or more sensors. The system generates synthetic data by introducing one or more simulated modifications to sensor data captured by the sensors or by simulating the sensor data for a virtual environment. The autonomous control system uses the synthetic data to train computer models for various detection and control algorithms. In general, this allows autonomous control systems to augment training data to improve performance of computer models, simulate scenarios that are not included in existing training data, and/or train computer models that remove unwanted effects or occlusions from sensor data of the environment.Type: GrantFiled: June 8, 2020Date of Patent: November 1, 2022Assignee: Tesla, Inc.Inventors: Forrest Nelson Iandola, Donald Benton MacMillen, Anting Shen, Harsimran Singh Sidhu, Paras Jagdish Jain
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Patent number: 11361457Abstract: An annotation system uses annotations for a first set of sensor measurements from a first sensor to identify annotations for a second set of sensor measurements from a second sensor. The annotation system identifies reference annotations in the first set of sensor measurements that indicates a location of a characteristic object in the two-dimensional space. The annotation system determines a spatial region in the three-dimensional space of the second set of sensor measurements that corresponds to a portion of the scene represented in the annotation of the first set of sensor measurements. The annotation system determines annotations within the spatial region of the second set of sensor measurements that indicates a location of the characteristic object in the three-dimensional space.Type: GrantFiled: July 17, 2019Date of Patent: June 14, 2022Assignee: Tesla, Inc.Inventor: Anting Shen
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Publication number: 20220043449Abstract: An autonomous control system combines sensor data from multiple sensors to simulate sensor data from high-capacity sensors. The sensor data contains information related to physical environments surrounding vehicles for autonomous guidance. For example, the sensor data may be in the form of images that visually capture scenes of the surrounding environment, geo-location of the vehicles, and the like. The autonomous control system simulates high-capacity sensor data of the physical environment from replacement sensors that may each have lower capacity than high-capacity sensors. The high-capacity sensor data may be simulated via one or more neural network models. The autonomous control system performs various detection and control algorithms on the simulated sensor data to guide the vehicle autonomously.Type: ApplicationFiled: October 22, 2021Publication date: February 10, 2022Inventors: Forrest Nelson Iandola, Donald Benton MacMillen, Anting Shen, Harsimran Singh Sidhu, Daniel Paden Tomasello, Rohan Nandkumar Phadte, Paras Jagdish Jian
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Patent number: 11157014Abstract: An autonomous control system combines sensor data from multiple sensors to simulate sensor data from high-capacity sensors. The sensor data contains information related to physical environments surrounding vehicles for autonomous guidance. For example, the sensor data may be in the form of images that visually capture scenes of the surrounding environment, geo-location of the vehicles, and the like. The autonomous control system simulates high-capacity sensor data of the physical environment from replacement sensors that may each have lower capacity than high-capacity sensors. The high-capacity sensor data may be simulated via one or more neural network models. The autonomous control system performs various detection and control algorithms on the simulated sensor data to guide the vehicle autonomously.Type: GrantFiled: December 27, 2017Date of Patent: October 26, 2021Assignee: Tesla, Inc.Inventors: Forrest Nelson Iandola, Donald Benton MacMillen, Anting Shen, Harsimran Singh Sidhu, Daniel Paden Tomasello, Rohan Nandkumar Phadte, Paras Jagdish Jain
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Publication number: 20200401136Abstract: An autonomous control system generates synthetic data that reflect simulated environments. Specifically, the synthetic data is a representation of sensor data of the simulated environment from the perspective of one or more sensors. The system generates synthetic data by introducing one or more simulated modifications to sensor data captured by the sensors or by simulating the sensor data for a virtual environment. The autonomous control system uses the synthetic data to train computer models for various detection and control algorithms. In general, this allows autonomous control systems to augment training data to improve performance of computer models, simulate scenarios that are not included in existing training data, and/or train computer models that remove unwanted effects or occlusions from sensor data of the environment.Type: ApplicationFiled: June 8, 2020Publication date: December 24, 2020Inventors: Forrest Nelson Iandola, Donald Benton MacMillen, Anting Shen, Harsimran Singh Sidhu, Paras Jagdish Jain
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Patent number: 10872251Abstract: An annotation system provides various tools for facilitating training data annotation. The annotation tools include a bidirectional annotation model that generates annotations for an image sequence based on both forward information and backward information in an image sequence. The annotation system also facilitates annotation processes by automatically suggesting annotations to the human operator based on a set of annotation predictions and locations of interactions of the human operator on the image. This way, the annotation system provides an accelerated way to generate high-quality annotations that take into account input from a human operator by using the predictions as a guide when it appears that an estimated annotation is consistent with the judgement of the human operator. The annotation system also updates annotations for an overlapping set of objects based on input from human operators.Type: GrantFiled: July 10, 2018Date of Patent: December 22, 2020Assignee: Tesla, Inc.Inventors: Anting Shen, Forrest Nelson Iandola
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Patent number: 10678244Abstract: An autonomous control system generates synthetic data that reflect simulated environments. Specifically, the synthetic data is a representation of sensor data of the simulated environment from the perspective of one or more sensors. The system generates synthetic data by introducing one or more simulated modifications to sensor data captured by the sensors or by simulating the sensor data for a virtual environment. The autonomous control system uses the synthetic data to train computer models for various detection and control algorithms. In general, this allows autonomous control systems to augment training data to improve performance of computer models, simulate scenarios that are not included in existing training data, and/or train computer models that remove unwanted effects or occlusions from sensor data of the environment.Type: GrantFiled: March 23, 2018Date of Patent: June 9, 2020Assignee: Tesla, Inc.Inventors: Forrest Nelson Iandola, Donald Benton MacMillen, Anting Shen, Harsimran Singh Sidhu, Paras Jagdish Jain
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Publication number: 20200175326Abstract: Systems and methods for enhanced object detection for autonomous vehicles based on field of view. An example method includes obtaining an image from an image sensor of one or more image sensors positioned about a vehicle. A field of view for the image is determined, with the field of view being associated with a vanishing line. A crop portion corresponding to the field of view is generated from the image, with a remaining portion of the image being downsampled. Information associated with detected objects depicted in the image is outputted based on a convolutional neural network, with detecting objects being based on performing a forward pass through the convolutional neural network of the crop portion and the remaining portion.Type: ApplicationFiled: December 4, 2019Publication date: June 4, 2020Inventors: Anting Shen, Romi Phadte, Gayatri Joshi
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Publication number: 20200175401Abstract: Systems and methods include machine learning models operating at different frequencies. An example method includes obtaining images at a threshold frequency from one or more image sensors positioned about a vehicle. Location information associated with objects classified in the images is determined based on the images. The images are analyzed via a first machine learning model at the threshold frequency. For a subset of the images, the first machine learning model uses output information from a second machine learning model, the second machine learning model being performed at less than the threshold frequency.Type: ApplicationFiled: December 3, 2019Publication date: June 4, 2020Inventor: Anting Shen
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Publication number: 20200027229Abstract: An annotation system uses annotations for a first set of sensor measurements from a first sensor to identify annotations for a second set of sensor measurements from a second sensor. The annotation system identifies reference annotations in the first set of sensor measurements that indicates a location of a characteristic object in the two-dimensional space. The annotation system determines a spatial region in the three-dimensional space of the second set of sensor measurements that corresponds to a portion of the scene represented in the annotation of the first set of sensor measurements. The annotation system determines annotations within the spatial region of the second set of sensor measurements that indicates a location of the characteristic object in the three-dimensional space.Type: ApplicationFiled: July 17, 2019Publication date: January 23, 2020Inventor: Anting Shen
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Publication number: 20200019799Abstract: An annotation system provides various tools for facilitating training data annotation. The annotation tools include a bidirectional annotation model that generates annotations for an image sequence based on both forward information and backward information in an image sequence. The annotation system also facilitates annotation processes by automatically suggesting annotations to the human operator based on a set of annotation predictions and locations of interactions of the human operator on the image. This way, the annotation system provides an accelerated way to generate high-quality annotations that take into account input from a human operator by using the predictions as a guide when it appears that an estimated annotation is consistent with the judgement of the human operator. The annotation system also updates annotations for an overlapping set of objects based on input from human operators.Type: ApplicationFiled: July 10, 2018Publication date: January 16, 2020Inventors: Anting Shen, Forrest Nelson Iandola